About the role
We are looking for a Senior AI/ML expert with a combination of Engineering/Applied Research experience to help us develop our foundational logical reasoning AI system. You will have worked in AI/ML for several years to have experienced, researched/applied different neural network architectures to various problems (e.g. natural language, vision, graphs, symbolic, formal domains), using several model training and optimization techniques (e.g. value models, reinforcement learning, search strategies), and across modalities (text, audio, video). A strong track record in graphs (graph theory, GNNs, GraphML, etc.), and ML-based code synthesis and/or validation will be invaluable. We are especially keen on candidates who have applied ML to real-world physical/materials/etc. engineering applications/use cases – either directly as a full-time or even as an expert consultant across industries/domains.
Key responsibilities
- Design, develop, deploy and evaluate novel machine learning models and algorithms to solve theorem proving as a foundational framework to developing logical reasoning in AI
- Apply various ML techniques, including supervised, unsupervised, and reinforcement learning
- Work with large datasets to preprocess, clean, and transform data for model training and evaluation
- Implement data pipelines and ETL processes to ensure efficient data flow and accessibility
- Design and conduct experiments, analyze results, develop metrics and benchmarks profile and optimize the performance of machine learning models
Desired Experience & Qualifications
- Bachelor's, Master’s, or Ph.D. in Computer Science, Engineering, Mathematics, or a related field
- 1+ years in machine learning, AI, or related fields
- Proven experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn
- Experience with data engineering tools and platforms such as Apache Spark, Hadoop, or similar
- Experience with MLOps practices and tools for model deployment, monitoring and logging such as Prometheus, Grafana, or ELK stack
- Experience with deep learning architectures and techniques, especially across domains, including vision, natural language, graphs; bonus for other NN architectures, e.g. symbolic, GraphML, etc
- Experience with program/code synthesis or models focused on systems design generation
- Experience applying ML to various real-world and engineering use cases
- Familiarity with cloud platforms and their ML toolkits, especially containerization and orchestration tools such as Docker and Kubernetes
- Familiarity with CI/CD tools like Jenkins, GitLab CI, or CircleCI
- Contributions to open-source projects in machine learning or AI communities
Hummingbird Bioscience is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all Singapore and US federal, state and local laws and/or guidelines that prohibit employment discrimination on the basis of age, race, color, gender, sexual orientation, gender identity, ethnicity, national origin, citizenship, religion, genetic carrier status, disability, pregnancy, childbirth or related medical conditions, marital status, protected veteran status and other protected classifications.
