PbAbout Turing: /b /ppBased in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the PL /ppbr/ppbRole Overview: /b /ppTuring is seeking a bhands-on Machine Learning Senior Staff Engineer /bto lead cross-functional teams building and deploying cutting-edge LLM and ML systems. In this role, you’ll drive the full lifecycle of AI development — from research and large-scale model training to production deployment — while mentoring top engineers and collaborating closely with research and infrastructure leaders. /ppbr/ppYou’ll combine btechnical depth in deep learning and MLOps /b with bleadership in execution and strategy /b, ensuring that Turing’s AI initiatives deliver reliable, high-performance systems that translate research breakthroughs into measurable business impact. /ppbr/ppThis position is ideal for leaders who are still bcomfortable coding, optimizing large-scale training pipelines /b, building collab notebooks that break the models and bnavigating the intersection of research, engineering, and product delivery /b. /ppbr/ppbRoles Responsibilities: /b /pulliLead and mentor a cross-functional team of ML engineers, data scientists, and MLOps professionals. /liliOversee the full lifecycle of LLM and ML projects — from data collection to training, evaluation, and deployment. /liliCollaborate with Research, Product, and Infrastructure teams to define goals, milestones, and success metrics. /liliProvide technical direction on large-scale model training, fine-tuning, and distributed systems design. /liliImplement best practices in MLOps, model governance, experiment tracking, and CI/CD for ML. /liliManage compute resources, budgets, and ensure compliance with data security and responsible AI standards. /liliCommunicate progress, risks, and results to stakeholders and executives effectively. /liliOverlap of 6 hours with PST time zone is mandatory. /li /ulpbr/ppbRequired Skills Qualifications: /b /pulliStrong background in Machine Learning, NLP, and modern deep learning architectures (Transformers, LLMs). /liliHands-on experience with frameworks such as PyTorch, TensorFlow, Hugging Face, or DeepSpeed /liliHands-on experience in Docker for Production deployment. /liliProven experience managing teams delivering ML/LLM models in production environments. /liliKnowledge of distributed training, GPU/TPU optimization, and cloud platforms (AWS, GCP, Azure). /liliFamiliarity with MLOps tools like MLflow, Kubeflow, or Vertex AI for scalable ML pipelines. /liliExcellent leadership, communication, and cross-functional collaboration skills. /liliBachelor’s or Master’s in Computer Science, Engineering, or related field (PhD preferred). /li /ulpbr/ppbNice to Have: /b /pulliExperience building Agentic applications /liliExperience training or fine-tuning foundation models. /liliContributions to open-source ML or LLM frameworks. /liliUnderstanding of Responsible AI, bias mitigation, and model interpretability. /li /ulpbr/ppbPerks of Freelancing With Turing: /b /pulliWork in a fully remote environment /liliOpportunity to work on cutting-edge AI projects with leading LLM companies /li /ulpbr/ppbOffer Details: /b /pullibCommitments Required: /b At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST /lilibEmployment type: /b Contractor assignment (no medical/paid leave) /lilibDuration of contract: /b 2 months; (expected start date is next week) /liliTimezone : US PST ( 6 hours overlap required 12pm PST to 6pm PST) /li /ulpbr/ppbEvaluation Process (approximately 120 mins): /b /pulliTwo rounds of interviews (60 min technical + 60 min technical cultural discussion) /li /ulpbr/ppbAfter applying, you will receive an email with a login link. Please use that link to access the portal and complete your profile. /b /ppbr/ppKnow amazing talent? Refer them at turing.com/referrals, and earn money from your network. /p