Senior Data Scientist

Senior Data Scientist / MLOps (LLMs / SLMs) Remote (U.S. time zones preferred) | Senior / Lead Level (5–8 years) | No C2C Our client is seeking a Senior Data Scientist / MLOps expert to lead the development and deployment of cutting-edge Small Language Model (SLM) solutions powering customer-facing AI products. This is a highly impactful role where you’ll own the end-to-end model lifecycle - from evaluation design to production deployment - and directly shape how AI is used in a specialized, high-stakes domain. Responsibilities: • Own the full lifecycle of LLM/SLM development: evaluation, fine-tuning, and production deployment • Design and implement model evaluation frameworks focused on accuracy, reliability, and low hallucination rates • Lead model selection and benchmarking across candidate models • Build and optimize training pipelines (cloud GPU environments, scalable workflows) • Develop and manage fine-tuning strategies (SFT, LoRA/QLoRA, instruction tuning, alignment methods) • Own model serving, inference performance, and monitoring (latency, cost, quality metrics) • Partner cross-functionally with product and engineering teams to translate user feedback into model improvements • Establish reproducible experimentation and model versioning practices Qualifications: • 5–8 years of experience in data science, machine learning, or MLOps • 2+ years hands-on experience with LLMs/SLMs (fine-tuning, evaluation, deployment) • Proven track record of shipping ML models into production environments • Strong Python skills and experience with ML ecosystems (PyTorch, Hugging Face, etc.) • Experience with RAG systems, model evaluation, and benchmarking • Familiarity with cloud platforms (AWS, GCP, or Azure) and GPU-based training • Solid understanding of experimentation and statistical evaluation methods • Strong communication skills with the ability to document findings and drive decisions Nice to Have: • Experience with alignment methods (DPO, RLHF variants) • Synthetic data generation or distillation approaches • Model serving and optimization tools (vLLM, Triton, etc.) • Experience in regulated or high-accuracy domains (e.g., legal, healthcare, compliance) • Contributions to open-source or published research in NLP/AI Why Join: • Work on real-world AI applications where accuracy and trust are critical • Own outcomes - not just tasks - in a fast-moving, high-impact environment • Collaborate with a highly technical, product-driven team • Opportunity to shape evaluation standards and best practices in applied AI Salary Range or 1099 Rate compensation varies depending on experience.