Senior Data Scientist

We're Hiring: ML/AI Engineer (Data Science Focus) | Join Simplify Healthcare

Simplify Healthcare is on a mission to revolutionize online AI-driven workflows with intelligent, context-aware AI agents. We’re searching for an ML/AI Engineer (Data Science Focus) to drive excellence and innovation in our platform.

If you're passionate about bridging traditional data science with cutting-edge generative AI, love challenges like enhancing retrieval algorithms, fine-tuning LLMs, or optimizing the intersection of data and AI, we want YOU on our team.

Location: Hybrid/Remote

Role Type: Full-Time | Engineering

Experience: 4–7 years in Data Science, Machine Learning, or Applied AI

What You’ll Do

As our ML/AI Engineer , here’s what your day-to-day might look like:

Advanced Retrieval & Optimization:

Design and implement next-level Retrieval Augmented Generation (RAG) systems for document and web scraping agents. Move beyond basic semantic search by combining keyword + dense vector search, optimizing document chunking, and incorporating Cross-Encoder reranking (Cohere, BGE) to amplify AI context relevance.

Data Engineering Superpower:

Craft end-to-end data pipelines to handle complex structured and unstructured data for integration into our vector databases like Qdrant or PostgreSQL (pgvector). Accuracy starts with clean data—you’ll ensure ours is pristine.

LLM Fine-Tuning & Deployment:

Fine-tune cutting-edge LLMs such as Llama 3 and Mistral using techniques like LoRA/QLoRA. Reduce latency and costs while improving accuracy, and deploy models via high-throughput engines like vLLM or Ray Serve.

⚙️ LLMOps Mastery:

Implement automated evaluation systems (using tools like RAGAS, TruLens) to measure and refine performance metrics. Continuously optimize our systems by minimizing hallucination and improving retrieval precision.

Blend Traditional ML with AI Innovation:

Develop classifiers, NER solutions, and other ML models to complement workflows. Support deterministic pre-processing alongside generative AI layers.

Collaborate Across Teams:

Partner with Senior AI Technical Leads and Full Stack Developers to refine system prompts and serve scalable AI endpoints using FastAPI.

Our Ideal Candidate

You're an analytical problem-solver who obsesses over data quality, accuracy, and stability. You balance theoretical AI research with the engineering practicality of shipping production-grade solutions. Here’s what makes you shine:

✅ Minimum 4–7 years of experience in Machine Learning, Data Science, or Applied AI Engineering.

✅ Exceptional, production-level Python skills , along with SQL mastery for data management.

✅ Deep math and practical understanding of embeddings, vector search techniques, and NLP methodologies.

✅ Proven experience deploying open-source models and working with LLM APIs (OpenAI, Anthropic, HF Transformers).

✅ Bonus: Played a critical role in building ML systems powering Doc Agents, Web Scraping Agents, RAG frameworks, Voice Agents, or Data Builders .

Your Toolkit ️

Here’s the tech stack you’ll work • Languages: Python (Expert), SQL (Advanced) • AI/ML Tools: PyTorch, Hugging Face, NumPy, Scikit-learn, Pandas, NLTK/SpaCy • GenAI/RAG Frameworks: LlamaIndex, LangChain, OpenAI/Anthropic APIs • Databases: Qdrant, PostgreSQL (pgvector), Supabase • LLMOps: RAGAS, TruLens, Langfuse, W&B • Infrastructure: Docker, Git, CI/CD for MLOps

Interested in joining a high-impact team at the forefront of AI innovation? Apply now and simplify the complex, with SimplifyHealthcare.

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