Total 41 job vacancies by Ariston Services Pte. Ltd.

Job Description:

Candidate requires to have SAP FICO (& MM preferred) for supporting daily operations / implementing new change requests.

SAP FICO domain (general ledger, account receivable, account payable, payment processes, bank statements, procurement to pay, asset module).

Candidate needs to handle the incidents, service requests, change requests independently, understand the functional requirements, able to do root cause analysis, communicate with business users and resolve the issues within the SLA’s.

Candidate also preferred to be able to perform technical SAP ABAP debugging and simple coding.

ROLES & RESPONSIBILITIES:

- Perform monitoring activities using tools provided as well as reviews of transactions flagged out

- Ensure that all tasks are completed/submitted in accordance to Standard Operating Procedures within the agreed timelines/SLA.

- Ensure proper documentation, notification, escalation, tracking and follow up of all interactions with client

- Handle ad hoc duties as required

REQUIREMENTS:

- Minimum 1 year of experience working in an administrative role

- Minimum education level: N levels subject to working experience

- Fast learner and good team player

- Demonstrates good communication skills and comfortable to work in a fast-paced environment

- Working/shift hours are 10am-10pm, 4 days a week

- Able to work rotating shift hours including weekends and public holidays

· Administration experience of Storage Arrays of multiple vendors like EMC, Hitachi and Netapp

· Administration experience of Different Cloud platforms like AWS and Azure.

· Hitachi midrange and enterprise storage (AMS, HUS, VSP & Gx00 etc)

· Experience on AWS CloudSpecific technologies like EC2, S3, Route53, Cloud Formation, Elastic IPs, VPC, RDS and Cloud Watch.

· Configuring Elastic Load Balancers with EC2 Auto Scaling groups.

· Optimized Volumes and EC2 Instances and created multi AZ VPC Instances

· Good Understanding of AWS Elastic Block storage(EBS), various volume types and Utilization of different types of EBS Volumes based on client requirement.

· Storage performance tuning and troubleshooting.

· Incident management and change management process knowledge.

· Project handling experience from sizing to roll-out, preferably with project management background
Strong analytical skill, very initiative, good planning & systematic execution

• RESPONSIBILITIES:
• Collaborate with the Project Team in understanding client requirements and how they translate in application features
• Collaborate with the Team to set specifications for new / existing applications
• Participate in incident management and change requests
• Perform troubleshooting and debugging of applications when required
• Evaluate existing applications to reprogram, update and add new features Work with business process owners/SMEs to assess capabilities and identify high-level user requirements
• Work with project managers, architects and SMEs to define metrics and performance goals for the process.
• Participate in transitioning the requirements and use cases.

Skills which are good to have / optional
• Experience in executing project releases on Pega PRPC BPM platform.
• Exposure in executing large BPM engagements through the complete SDLC lifecycle.
• Experience in PEGA technical and architecture with broad industry and functional knowledge
• PEGA certified i.e. SA, SSA, LSAComments for Suppliers:Top Mandatory skills

MUST BRING:

Prior hands-on experience in Pega Development (preferably 6 months or more)

Critical Success Factors
Mandatory
• Prior hands-on experience in Pega Development (preferably 6 months or more)

Good to have but not a must
• Experience in executing project releases on Pega PRPC BPM platform.
• Exposure in executing large BPM engagements through the complete SDLC lifecycle.
• Experience in PEGA technical and architecture with broad industry and functional knowledge
• PEGA certified i.e. SA, SSA, LSA

Responsibilities include but are not limited to:
• Collaborate with the Project Team in understanding client requirements and how they translate in application features
• Collaborate with the Team to set specifications for new / existing applications
• Participate in incident management and change requests
• Perform troubleshooting and debugging of applications when required
• Evaluate existing applications to reprogram, update and add new features Work with business process owners/SMEs to assess capabilities and identify high-level user requirements
• Work with project managers, architects and SMEs to define metrics and performance goals for the process.
• Participate in transitioning the requirements and use cases.

· Manage and ensure timely deliverables by the system Maintenance Vendor; ensure deliverables conform to the standards and control defined for the Programme; identify and manage risk and mitigation strategies; identify, analyse and ensure resolution of issues; manage change control; track and escalate risks and issues to * PM and Ops Manager; perform project planning with the system maintenance team, Interfacing team, Infra team, etc.

· Seek Ops Manager’s approval of system changes including funding and implementation and completion of milestone, etc; consolidate and prepare submission for Performance Management Report (PMR)/ Post Implementation Review (PIR) and update * PM and Ops Manager.

· Manage Change Request (CR). Responsibilities include tracking of CR raised; monitoring the status of CR from requirement initiation to implementation and working with various parties to address issues impeding the progress of the review of CR effort; assessing impact and solution proposed by the system Maintenance Vendor; facilitating users in CR testing and ensuring testing is complete and comprehensive.

· Provide analysis and consultation services to address operational issues and audit related activities.

· Coordinate and perform secretariat role for meetings with different stakeholders and internal team meetings.

· Oversee and participate in requirements gathering and evaluate requirements & design solutions with the system Maintenance Vendor.

· Facilitate HR systems training for users.

· Manage Service Request (SR). Responsibilities include monitoring of the SR raised and assessing impact with the system Maintenance Vendor.

· Manage System Investigation Request (SIR)/ Problem Report (PR). Track SIRs and system defects reported by users. Ensure prompt resolution is provided by the system Maintenance Vendor to the defects reported, and prompt clarifications are provided for SIRs.

· Monitor the progress of outstanding tasks to be completed by the system Maintenance Vendor or users; ensure timely and complete resolution of such tasks, deliverables to conform to the standards and control defined for the Programme.

· Monitor and track the closure of follow-ups for batch job failures.

· Provide support to the system reporting and data patching team on queries from functional perspective.

· Perform project planning with system Maintenance Vendor, Interfacing team, Infra Team, external systems, etc.

· Propose, document and implement improvements to the current work processes to achieve increased efficiency and effectiveness or tighten audit issues in delivering the maintenance support services.

Review, propose and update changes to the documentation where necessary.

Required Working Experience

· At least 4 years of working experience in information technology of which at least 2 years of working experience in SAP ERP.

· Experience in SAP HCM ERP is preferred.

· Experience in SG Government HCM projects is preferred.

Must-Have Skills:

• Cloud services - AWS EKS, ECR, IAM, API GW, Lambda, CDN, WAF, VPC, TGW
• DevSecOps skills - Jenkins (Cloudbees), SonarQube, JFrog Artifactory, Foritfy WebInspect, Snyk, Jira SAAS, Bitbucket SAAS, Confluence SAAS
• Migration Experience - Platform A(selfhosted) to Platform B (SAAS) , Platform A(Self-hosted) to Platform A(SAAS)
• Desirable - Basic knowledge about Managed File Transfer, MuleSoft,

• Support Programme Governance and ensure deliverables are completed in a timely manner and as per scope using varied project delivery methodologies (Waterfall/Agile/Hybrid)
• Have a consulting mindset and able to contribute in developing framework & methodologies
• Oversee quality of Programme deliverables throughout the delivery lifecycle by performing quality assurance to facilitate adherence to standards and processes through Quality gates/SDLC governance.
• Proactively take ownership of own activities with minimal supervision and flexible in managing adhoc workload as required
• Attend and manage meetings by preparing invites, decks, consolidating agenda items, creation & circulation of minutes and follow up on action items in a timely manner
• Able to facilitate/lead a discussion with Project stakeholders and drive specific agenda items / discussions
• Skilled in facilitating and tracking medium to complex Project plan activities using Microsoft Project Plan (MPP)
• Manage and oversee the reporting and able to use tracking tools of Confluence, ADO (Azure DevOps) and MS Office tools like MS PowerPoint & Excel
• Perform any additional administrative activities as required

Skillset

• Previous Experience working on Banking / Financial Services (Must have)
• Experience in supporting Programmes/Projects with knowledge in planning, reporting & delivery governance
• Detail oriented and analytical, to be able to analyze situations and perform well in a dynamic environment
• Experience and exposure to different project methodologies (preferable)
• Hands-on experience of using Project Management Tool - (MPP) Microsoft Project in running Project schedule management (Must have)
• Hands-on experience on Microsoft Office tools - PowerPoint & Excel in creating reports and trackers (Must have)
• Team player and able to work collaboratively with others (Must have)
• Excellent communication (both written and verbal) and stakeholder management skills (Must have)
• About 5-10 years of experience (preferable)

Job description

• Support Programme Governance and ensure deliverables are completed in a timely manner and as per scope using varied project delivery methodologies (Waterfall/Agile/Hybrid)
• Have a consulting mindset and able to contribute to developing framework & methodologies
• Oversee quality of Programme deliverables throughout the delivery lifecycle by performing quality assurance to facilitate adherence to standards and processes through Quality gates/SDLC governance.
• Proactively take ownership of own activities with minimal supervision and flexible in managing adhoc workload as required
• Attend and manage meetings by preparing invites, decks, consolidating agenda items, creation & circulation of minutes and follow up on action items in a timely manner
• Able to facilitate/lead a discussion with Project stakeholders and drive specific agenda items / discussions
• Manage and oversee the reporting and able to use tracking tools of Confluence, ADO (Azure DevOps) and MS Office tools like MS PowerPoint & Excel
• Perform any additional administrative activities as required

Skillset

• Previous Experience working on Banking / Financial Services (Must have)
• Experience in Business Analysis / Project Management with exposure to planning, reporting & delivery governance
• Detail oriented and analytical, to be able to analyze situations and perform well in a dynamic environment
• Experience and exposure to different project methodologies (preferable)
• Hands-on experience on Microsoft Office tools - PowerPoint & Excel in creating reports and trackers (Must have)
• Team player and able to work collaboratively with others (Must have)
• Excellent communication (both written and verbal) and stakeholder management skills (Must have)
• About 5-10 years of experience (preferable)

Role Summary

· Lead and manage Data, and AI Consulting projects from inception to completion, ensuring successful delivery within budget and timeline constraints.

· Collaborate with clients to understand their business goals and challenges and develop AI strategies and roadmaps to address their needs.

· Identify and evaluate Data transformation opportunities within client organisations to enable them to be AI-ready, conducting feasibility studies and assessing potential risks and benefits.

· Provide guidance and mentorship to junior consultants, fostering their professional growth and development in Data, AI and consulting domains.

· Stay up to date with the latest advancements in AI technologies and methodologies, leverage them for client projects and accelerate innovation and growth through the development of service offerings

· Collaborate with cross-functional teams, including data scientists, data engineers, business analysts, and industry experts to ensure seamless integration and implementation of Data transformation solutions enabling organising scale with AI.

· Build and maintain strong relationships with clients, acting as a trusted advisor and thought leader in Data, AI, and Consulting.

Key skills:

· Well-defined strong management consulting experience across Banking- Finance or Telco

· Develop, lead and drive teams to achieve bespoke outcomes.

· Ability to design Operating & Business Models specific to data platforms and emerging industry capabilities - mandatory.

· Experience in leading RFP/Tender responses on a large scale with revenue targets.

· Demonstrated ability in defining and delivering hybrid & multi-cloud strategy/roadmap, migration, and adoption.

· Experience with Cloud domain (AWS, Azure, Google, private cloud providers) which could be led through digital transformation and/or migration projects.

· Understanding of emerging business priorities like Application Portfolio Rationalization, AI, and ML

Technology strategy transformation, “Business of IT” analysis

Roles:
● Senior Automation Specialist and Lead Software Developer.
● Engineering and Architecture of application automated deployment and hosting

Responsibilities:
● Source Development, enhancement and maintenance using Java J2EE.
● Automation on application readiness and deployment automation through ADO / Jenkins pipelines with certificate consolidation, SonarQube Code Coverage, Git Leaks and Vulnerability handling.
● Source routings, service integrations and bean management through Apache Camel.
● API Integration with banking internal applications with SOAP and REST Interface. Solace Integration with JMS Listeners for Topic and Queue handling using Java and Apache Camel.
● Design and implementation of Plugins, Automations and Tool development for Orchestration tools like Rundeck Pro Orchestrator by Pager Duty.
● Automation and managing the engineering side of the tool, version upgrades and stakeholder relationship towards enhancing the product and production support including container platform.
● Experience in API and Rundeck Plugin automation developments to standardize Banks Security for the tools we support using Java
● Development for integration of Dev and Ops activities to achieve Automated DevOps Standard workflow
● BAU Support on critical releases, DR Drills, production issues and functional implementations.
● Kibana Dashboard / VIs creation (With Elastic Indexes) for Data Analysis and Report preparation
● Complete documentation, presentations and User workshops about the product, user guide, implementation, etc.,

Your Role

As a Lead Data Engineer, you will play a leading role in designing, building, and optimizing our data infrastructure, ensuring that it supports the advanced analytics need of the bank. You will oversee a team of data engineers, working closely with data analysts, DevOps team, infrastructure engineers, and other stakeholders to deliver high-quality data solution.

Your main responsibilities will include:

· Design, develop, and implement Spark Scala applications and data processing pipelines to process large volumes of structured and unstructured data.

· Integrate Elasticsearch with Spark to enable efficient indexing, querying, and retrieval of data.

· Optimize and tune Spark jobs for performance and scalability, ensuring efficient data processing and indexing in Elasticsearch.

· Collaborate with data engineers, data scientists, and other stakeholders to understand requirements and translate them into technical specifications and solutions.

· Design and deploy data engineering solutions on OpenShift Container Platform (OCP) using containerization and orchestration techniques.

· Optimize data engineering workflows for containerized deployment and efficient resource utilization.

· Collaborate with DevOps teams to streamline deployment processes, implement CI/CD pipelines, and ensure platform stability.

· Monitor and optimize data pipeline performance, troubleshoot issues, and implement necessary enhancements.

· Implement monitoring and logging mechanisms to ensure the health, availability, and performance of the data infrastructure.

· Document data engineering processes, workflows, and infrastructure configurations for knowledge sharing and reference.

· Stay updated with emerging technologies, industry trends, and best practices in data engineering and DevOps.

· Provide technical leadership, mentorship, and guidance to junior team members to foster a culture of continuous learning and innovation to the continuous improvement of the analytics capabilities within the bank.

Requirements

· Bachelor's degree in Computer Science, Data Engineering, Information Technology, or a related field.

· At least 10 years of experience as a Data Engineer, working with Hadoop, Spark, and data processing technologies in large-scale environments.

· Strong expertise in designing and developing data infrastructure using Hadoop, Spark, and related tools (HDFS, Hive, Ranger, etc)

· Experience with containerization platforms such as OpenShift Container Platform (OCP) and container orchestration using Kubernetes.

· Proficiency in programming languages commonly used in data engineering, such as Spark, Python, Scala, or Java.

· Knowledge of DevOps practices, CI/CD pipelines, and infrastructure automation tools (e.g., Docker, Jenkins, Ansible, BitBucket)

· Experience with Grafana, Prometheus, Splunk will be an added benefit

· Strong problem-solving and troubleshooting skills with a proactive approach to resolving technical challenges.

· Excellent collaboration and communication skills to work effectively with cross-functional teams.

· Ability to manage multiple priorities, meet deadlines, and deliver high-quality results in a fast-paced environment.

· Experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services is a plus.

Your Role

As an ML Engineer, your pivotal role involves operationalizing ML Models developed by CLIENT’s data scientists. You will serve as the focal point for ML model refactoring, optimization, containerization, deployment, and quality monitoring.

Your main responsibilities will include:

• Conduct reviews for compliance of the ML models in accordance with overall platform governance principles such as versioning, data / model lineage, code best practices and provide feedback to data scientists for potential improvements
• Develop pipelines for continuous operation, feedback and monitoring of ML models leveraging best practices from the CI/CD vertical within the MLOps domain. This can include monitoring for data drift, triggering model retraining and setting up rollbacks.
• Optimize AI development environments (development, testing, production) for usability, reliability and performance.
• Have a strong relationship with the infrastructure and application development team in order to understand the best method of integrating the ML model into enterprise applications (e.g., transforming resulting models into APIs).
• Work with data engineers to ensure data storage (data warehouses or data lakes) and data pipelines feeding these repositories and the ML feature or data stores are working as intended.
• Evaluate open-source and AI/ML platforms and tools for feasibility of usage and integration from an infrastructure perspective. This also involves staying updated about the newest developments, patches and upgrades to the ML platforms in use by the data science teams.

Technical Skills

• Proficiency in Python used both for ML and automation tasks
• Good knowledge of Bash and Unix/Linux command-line toolkit is a must-have.
• Hands on experience building CI/CD pipelines orchestration by Jenkins, GitLab CI, GitHub Actions or similar tools is a must-have.
• Knowledge of OpenShift / Kubernetes is a must-have.
• Good understanding of ML libraries such as Panda, NumPy, H2O, or TensorFlow.
• Knowledge in the operationalization of Data Science projects (MLOps) using at least one of the popular frameworks or platforms (e.g., Kubeflow, AWS Sagemaker, Google AI Platform, Azure Machine Learning, DataRobot, Dataiku, H2O, or DKube).
• Knowledge of Distributed Data Processing framework, such as Spark, or Dask.
• Knowledge of Workflow Orchestrator, such as Airflow or Ctrl-M.
• Knowledge of Logging and Monitoring tools, such as Splunk and Geneos.
• Experience in defining the processes, standards, frameworks, prototypes and toolsets in support of AI and ML development, monitoring, testing and operationalization.
• Experience in ML operationalization and orchestration (MLOps) tools, techniques and platforms. This includes scaling delivery of models, managing and governing ML Models, and managing and scaling AI platforms.
• Knowledge of cloud platforms (e.g. AWS, GCP) would be an advantage.

Soft Skills

• Good knowledge of Devops process and principles
• Strong in Software Engineering fundamentals
• Excellent communication skills
• Attention to detail
• Analytical mind and problem-solving aptitude
• Strong Organizational skills
• Visual Thinking

Key Responsibilities

· As part of the Enterprise Analytics delivery team, the position will be responsible for the delivery of Enterprise Technology solutions, managing the quality of functional delivery and ensuring the implementation of agreed functional capability

· Good business domain knowledge in Enterprise Analytics

· Plan & collaborate across different application teams to manage technical and functional dependencies of the solution

· Collate, understand and finalize functional and technical requirements

· Provide status update related to technical delivery to Project Manager (PM)/ Program Manager on functional deliveries

· Provide Systems input to specification phase (effort estimates, high level delivery plan) based on impact assessment etc

· Partner with Architects and Development Lead to ensure solution design complies with enterprise design principles, security and control standards

· Partner with Development Manager in managing application teams to build the enhancements

· Partner with Test Manager to ensure completion of System Integration Testing (SIT), User Acceptance Testing (UAT), performance / load testing and application security testing with quality results

· Prepare and manage technical implementation plan across application teams - coordinate technical implementation activities across application teams to ensure non-event production cutover and adequate post implementation support

Escalate issues that impacts project schedule on timely basis and propose workarounds/resolutions

Key Requirements

Technical Skills & Experience

· Good track record in developing and delivering global/regional IT capabilities for a multi-national/regional company with annual budgetary responsibility

· Working closely with stakeholders to develop practical domain roadmaps to move the enterprise towards the future state vision, while taking into account business, technical and delivery constraints

· Experience in banking industry preferred

· Experience in implementing large-scale, highly available applications or other large project implementation

· Experience in service-oriented technologies

· Proven result-oriented person with a focus on delivery

· Experience in actual systems development work, with prior coding, functional specifications and technical specifications and systems development and testing experience

· Good understanding and experience in software development cycle

· Highly effective communicating with technical stakeholders, proficient communicating with non-technical stakeholders

Good problem solving, analytical, synthesis, system thinking and solutioning skills

Competencies

· Ability to communicate complex topics in an understandable way using a level of detail and terms appropriate to the situation

· Must be a good team player and able to drive consensus amongst stakeholders with conflicting viewpoints and objectives

· People and team management in a transversal function

· Ability to effectively communicate, interact with and influence technical associates, business and operational partners and executives

· Work effectively within a fast-paced, cohesive architecture team and willing to learn fast and adapt quickly to change

· Possess strong understanding of business strategies and able to translate them into concrete achievable action plans

· Able to collaborate and drive motivation across a diverse slate within and across teams and can deal with difficult conversations effectively

· Owns and enhances workflows and processes, and delegates with clear accountabilities across the teams to meet objectives / outcomes

· Promotes an environment of learning and development. Understand and develop team members and others to achieve their professional growth

· Related professional/technical qualification will be advantageous although not mandatory

Responsibilities:

· Implement data transformation, aggregation, and enrichment processes to support various data analytics and machine learning initiatives

· Collaborate with cross-functional teams to understand data requirements and translate them into effective data engineering solutions

· Ensure data quality and integrity throughout the data processing lifecycle

· Design and deploy data engineering solutions on OpenShift Container Platform (OCP) using containerization and orchestration techniques

· Optimize data engineering workflows for containerized deployment and efficient resource utilization

· Collaborate with DevOps teams to streamline deployment processes, implement CI/CD pipelines, and ensure platform stability

· Implement data governance practices, data lineage, and metadata management to ensure data accuracy, traceability, and compliance

· Monitor and optimize data pipeline performance, troubleshoot issues, and implement necessary enhancements

· Implement monitoring and logging mechanisms to ensure the health, availability, and performance of the data infrastructure

· Document data engineering processes, workflows, and infrastructure configurations for knowledge sharing and reference

· Stay updated with emerging technologies, industry trends, and best practices in data engineering and DevOps

· Provide technical leadership, mentorship, and guidance to junior team members to foster a culture of continuous learning and innovation to the continuous improvement of the analytics capabilities within the bank

Requirements:

· Proven experience as a Data Engineer, working with Hadoop, Spark, and data processing technologies in large-scale environments

· Strong expertise in designing and developing data infrastructure using Hadoop, Spark, and related tools (HDFS, Hive, Pig, etc)

· Experience with containerization platforms such as OpenShift Container Platform (OCP) and container orchestration using Kubernetes

· Proficiency in programming languages commonly used in data engineering, such as Spark, Python, Scala, or Java

· Knowledge of DevOps practices, CI/CD pipelines, and infrastructure automation tools (e.g., Docker, Jenkins, Ansible, BitBucket)

· Experience with Graphana, Prometheus, Splunk will be an added benefit

· Strong problem-solving and troubleshooting skills with a proactive approach to resolving technical challenges

· Excellent collaboration and communication skills to work effectively with cross-functional teams

· Ability to manage multiple priorities, meet deadlines, and deliver high-quality results in a fast-paced environment

· Experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services is a plus

Your Role

As a Lead ML Engineer, you will play a leading role in operationalizing ML Models developed by CLIENT’s data scientists. You will serve as the focal point for ML model refactoring, optimization, containerization, deployment, and quality monitoring. Your main responsibilities will include:

• Conduct reviews for compliance of the ML models in accordance with overall platform governance principles such as versioning, data / model lineage, code best practices and provide feedback to data scientists for potential improvements
• Develop pipelines for continuous operation, feedback and monitoring of ML models leveraging best practices from the CI/CD vertical within the MLOps domain. This can include monitoring for data drift, triggering model retraining and setting up rollbacks.
• Optimize AI development environments (development, testing, production) for usability, reliability and performance.
• Have a strong relationship with the infrastructure and application development team in order to understand the best method of integrating the ML model into enterprise applications (e.g., transforming resulting models into APIs).
• Work with data engineers to ensure data storage (data warehouses or data lakes) and data pipelines feeding these repositories and the ML feature or data stores are working as intended.
• Evaluate open-source and AI/ML platforms and tools for feasibility of usage and integration from an infrastructure perspective. This also involves staying updated about the newest developments, patches and upgrades to the ML platforms in use by the data science teams.

Technical Skills

• At least 10 years of experience as a ML Engineer, working with Python, ML libraries, and large-scale data processing framework.
• Advance proficiency in Python used both for ML and automation tasks.
• Experience in working with ML libraries such as Panda, NumPy, H2O, or TensorFlow.
• Experience in working with large-scale data processing framework, such as Hadoop, Spark, or Dask.
• Knowledge of OpenShift / Kubernetes is a must-have.
• Good knowledge of Bash and Unix/Linux command-line toolkit is a must-have.
• Hands on experience building CI/CD pipelines orchestration by Jenkins, GitLab CI, GitHub Actions or similar tools is a must-have.
• Knowledge in the operationalization of Data Science projects (MLOps) using at least one of the popular frameworks or platforms (e.g., Kubeflow, AWS Sagemaker, Google AI Platform, Azure Machine Learning, DataRobot, Dataiku, H2O, or DKube).
• Knowledge of Workflow Orchestrator, such as Airflow or Ctrl-M.
• Knowledge of Logging and Monitoring tools, such as Splunk and Geneos.
• Experience in defining the processes, standards, frameworks, prototypes and toolsets in support of AI and ML development, monitoring, testing and operationalization.
• Experience in ML operationalization and orchestration (MLOps) tools, techniques and platforms. This includes scaling delivery of models, managing and governing ML Models, and managing and scaling AI platforms.
• Knowledge of cloud platforms (e.g. AWS, GCP) would be an advantage.

Soft Skills

• Good knowledge of Devops process and principles
• Strong in Software Engineering fundamentals
• Excellent communication skills
• Attention to detail
• Analytical mind and problem-solving aptitude
• Strong Organizational skills
• Visual Thinking