Machine Learning Engineer

Key Responsibilities:

• Design and develop a modular, scalable AI platform to serve foundation model and RAG-based applications.
• Build pipelines for embedding generation, document chunking, and indexing.
• Develop integrations with vector databases like Pinecone, Weaviate, Chroma, or FAISS.
• Orchestrate LLM flows using tools like LangChain, LlamaIndex, and OpenAI APIs.
• Implement RAG architectures to combine generative models with structured and unstructured knowledge sources.
• Create robust APIs and developer tools for easy adoption of AI models across teams.
• Build observability and monitoring into AI workflows for performance, cost, and output quality.
• Collaborate with DevOps, Data Engineering, and Product to align platform capabilities with business use cases.

Core Skill Set:

• Strong experience in Python, with deep familiarity in ML/AI frameworks (PyTorch, Hugging Face, TensorFlow).
• Experience building LLM applications, particularly using LangChain, LlamaIndex, and OpenAI or Anthropic APIs.
• Practical understanding of vector search, semantic retrieval, and embedding models.
• Familiarity with AI platform tools (e.g., MLflow, Kubernetes, Airflow, Prefect, Ray Serve).
• Hands-on with cloud infrastructure (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
• Solid grasp of RAG architecture design, prompt engineering, and model evaluation.
• Understanding of MLOps, CI/CD, and data pipelines in production environments.

Preferred Qualifications:

• Experience designing and scaling internal ML/AI platforms or LLMOps tools.
• Experience with fine-tuning LLMs or customizing embeddings for domain-specific applications.
• Contributions to open-source AI platform components.
• Knowledge of data privacy, governance, and responsible AI practices.

What You’ll Get:

• A high-impact role building the core AI infrastructure of our company.
• Flexible work environment and competitive compensation.
• Access to cutting-edge foundation models and tooling.
• Opportunity to shape the future of applied AI within a fast-moving team.