Machine Learning Engineer

Description :

- Collaborate closely with cross-functional teams including front-end, DevOps, and product to deliver high-quality software.

- Drive code excellence with rigorous unit/integration testing and code reviews.

- Monitor, debug, and optimize backend systems for enterprise-grade performance.

- Design high-performance, fault-tolerant systems capable of handling complex data workflows.

- Lead knowledge sharing, clear communication, and documentation for technical solutions.

- Coordinate effectively with remote global team members.

- Develop robust, scalable web applications tailored for B2B and enterprise client needs.

Required Skills and Experience :

- 7+ years building production-grade AIML systems (Python).

- Deep proficiency in LLM frameworks : LangChain, LlamaIndex, and custom RAG (Retrieval-Augmented Generation) pipelines.

- Strong background with vector databases and semantic search (Pinecone, Weaviate, FAISS, ChromaDB).

- Advanced prompt engineering and LLM fine-tuning for regulatory and compliance domains.

- NLP expertise : document processing, multi-format parsing (PDF, HTML, XML, Word), semantic embeddings.

- Hands-on work with Hugging Face Transformers (BERTRoBERTa, NER, text classification).

- Familiarity with LLM providers (OpenAI GPT-4, Anthropic Claude, Azure OpenAI, Llama, Mistral).

- Extensive cloud experience (AWS, Azure, Google Cloud Platform).

- Python async frameworks (FastAPI, asyncio, aiohttp); RESTful API design, JSON, OpenAPI/Swagger.

- Skilled with CI/CD tools (GitHub Actions, Jenkins, CodePipeline) and containerization (Docker, Kubernetes)

- Advanced database skills : PostgreSQL, MySQL, query optimization, indexing, schema design; NoSQL experience (MongoDB, DynamoDB).

- Git version control mastery, including complex workflows and resolution strategies.

- Familiarity with IaC tools (CloudFormation, Terraform).

Qualifications :

- Bachelors/Masters in Computer Science or related field.

- Track record of backend development in complex, scalable applications.

- Strong communication, collaboration, and stakeholder management skills[1].

- Experience with healthcare IT systems (HIS, EMR/EHR) and knowledge of data privacy

regulations (HIPAA, GDPR) is a plus.

- Cloud certifications and experience with AI-assisted development tools (GitHub Copilot) are highly desirable.

Soft Skills :

- Capable of working independently and leading technical discussions.

- Adaptable to fast-paced, agile environments.

Whats Offered :

- Competitive salary and benefits.

- Flexible hours, remote work options, and a collaborative, people-centred team.

- Opportunities to drive cutting-edge projects in the life science regulatory space.

- Supportive environment for professional development and growth.