Senior ML Engineer; GenAI

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• Design and implement end‑to‑end ML solutions from experimentation to production
• Build scalable ML pipelines and infrastructure
• Optimize model performance, efficiency, and reliability
• Write clean, maintainable, production‑quality code
• Conduct rigorous experimentation and model evaluation
• Troubleshoot and resolve complex technical challenges
• Mentor junior and mid‑level ML engineers
• Conduct code reviews and provide constructive feedback
• Share knowledge through documentation, presentations, and workshops
• Collaborate with cross‑functional teams (Dev Ops, Data Engineering, SAs)
• Contribute to internal ML practice development
• Stay current with ML research and emerging technologies
• Propose improvements to existing solutions and processes
• Contribute to the development of reusable ML accelerators
• Participate in technical discussions and architectural decisions

• Machine Learning Core: supervised, unsupervised, and reinforcement learning fundamentals
• Feature engineering, model training, evaluation, hyperparameter tuning, and validation
• Experience with classical ML libraries, Tensor Flow, PyTorch, or similar frameworks
• Deep learning: CNNs, RNNs, Transformers
• LLM applications: building production LLM‑based applications
• Prompt engineering and chain‑of‑thought strategies
• Retrieval‑augmented generation architectures and vector search
• Advanced proficiency in Python, pandas, numpy, and data processing libraries
• SQL and structured data handling
• ETL/ELT pipeline experience;
  Big Data frameworks (Spark or similar)
• Model deployment to production environments and containerization (Docker)
• CI/CD understanding for ML and model monitoring (MLflow, Weights & Biases, etc.)
• Cloud experience: AWS (Sage Maker, Lambda, etc.), GCP ML services, and cloud architecture
• Infrastructure‑as‑code tools (Terraform, Cloud Formation)

• Practical experience with cloud platforms (AWS stack preferred)
• Deep learning model expertise
• Experience with taxonomies or ontologies
• Pipeline orchestration for complex workflows
• Spark/Dask and Great Expectations knowledge

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.