ML Engineer

Actively Hiring

Full-time Posted 3 months ago

Responsibilities

check_circle Own the full model lifecycle: problem scoping, data exploration, feature engineering, algorithm selection, training, evaluation, and iterative improvement
check_circle Containerise and serve models via FastAPI based microservices; ensure low latency inference, monitoring, and automated rollback strategies
check_circle Build reproducible pipelines (training, validation, inference) with CI/CD and infrastructure as code practices
check_circle Work closely with data engineers, product managers, and domain experts to align ML solutions with business goals
check_circle Champion clean code, unit/integration testing, code reviews, and documentation for long-term maintainability
check_circle Stay up to date with the latest ML/AI advancements; prototype and benchmark new techniques (e.g., LLM fine-tuning, vector search, on-device ML). Diagnose and resolve production issues, optimise performance, and continually improve model robustness

Bachelor’s in CS, Data Science, AI, or equivalent; proven ML/DL production experience.
Expert in Python (NumPy, pandas, scikit-learn) and SQL; hands-on with PyTorch or TensorFlow; familiarity with Hugging Face.
Prompt engineering, RAG, vector search, and model monitoring; fine-tuning is an advantage; strong feature engineering and classical ML.
Docker, AWS (ECS/Fargate, S3, Lambda, SageMaker); CI/CD (Jenkins); MLflow or Metaflow; Prefect or Step Functions; MySQL and DynamoDB.
Strong problem-solving skills and data driven decision-making
Vigilant about data quality, edge cases, and performance bottlenecks
Open, constructive collaboration with cross functional teams; mentorship of junior engineers when required
Clear articulation of complex technical concepts to technical and nontechnical stakeholders Very good command of English, written and spoken

Machine Learning Data Science Pytorch Tensorflow Ai