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About Turing:

Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. Turing helps customers in two ways: Working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies.

Role Overview

We’re looking for a Data Scientist who has excellent hands on Python skills and Machine Learning experience  — someone who lives and breathes code, optimizes for performance, and has proven mastery on competitive programming or data challenge platforms like LeetCode, Codeforces, HackerRank, or Kaggle. In this role you will be working with Turing team members and AI researchers at Frontier Labs to devise techniques and build data sets to improve performance of models. 

What You’ll Do

• Build, test, and optimize high-performance Python systems used in large-scale AI and data pipelines.
• Design and maintain modular, clean, and production-ready Python codebases.
• Collaborate with cross-functional teams (data, infra, and research engineers) to deliver reliable backend components.
• Write efficient, maintainable, and testable code with strong focus on algorithms and data structures.
• Stay current with modern Python tools, frameworks, ML advancements and best practices.

Required Qualifications

• Bachelor’s or Master’s in Computer Science, Software Engineering, or a related field.
• 4+ years of professional experience writing Python in production environments.
• Expert-level proficiency in Python and core libraries (Pandas, NumPy, AsyncIO, Pytorch, Transformers, or similar).
• Proven track record on coding platforms — e.g., top percentile or strong rating on LeetCode, Codeforces, HackerRank, or Kaggle competitions.
• Experience with system design, clean architecture, and performance optimization.
• Working level Proficiency in either Machine Learning or Data Science for Machine Learning.

Bonus

• Recognized performance in Kaggle, Codeforces, or ICPC/TopCoder contests.
• Deep curiosity for performance tuning, scalability, and elegant code design.

Perks of Freelancing with Turing

• Work fully remotely, from anywhere.
• Collaborate with world-class AI labs and frontier research companies.
• Tackle real engineering challenges with high autonomy and ownership.

Offer Details

• Commitment: Minimum 20 hours/week with 4-hour PST overlap (options: 20, 30, or 40 hrs/week).
• Type: Contractor (no medical/paid leave).
• Duration: 3 months (start date: next week).

Evaluation Process

1. Technical Interview (60 mins): discussion of Python problem-solving, architecture, and system design.

About Turing:

Based 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 P&L

Role Overview

Turing is seeking a hands-on Machine Learning Senior Staff Engineer to 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.  

You’ll combine technical depth in deep learning and MLOps with leadership in execution and strategy, ensuring that Turing’s AI initiatives deliver reliable, high-performance systems that translate research breakthroughs into measurable business impact.

This position is ideal for leaders who are still comfortable coding, optimizing large-scale training pipelines, building collab notebooks that break the models and navigating the intersection of research, engineering, and product delivery.

Roles & Responsibilities

• Lead and mentor a cross-functional team of ML engineers, data scientists, and MLOps professionals.
• Oversee the full lifecycle of LLM and ML projects — from data collection to training, evaluation, and deployment.
• Collaborate with Research, Product, and Infrastructure teams to define goals, milestones, and success metrics.
• Provide technical direction on large-scale model training, fine-tuning, and distributed systems design.
• Implement best practices in MLOps, model governance, experiment tracking, and CI/CD for ML.
• Manage compute resources, budgets, and ensure compliance with data security and responsible AI standards.
• Communicate progress, risks, and results to stakeholders and executives effectively.
• Overlap of 6 hours with PST time zone is mandatory.

Required Skills & Qualifications

• Strong background in Machine Learning, NLP, and modern deep learning architectures (Transformers, LLMs).
• Hands-on experience with frameworks such as PyTorch, TensorFlow, Hugging Face, or DeepSpeed
• Hands-on experience in Docker for Production deployment. 
• Proven experience managing teams delivering ML/LLM models in production environments.
• Knowledge of distributed training, GPU/TPU optimization, and cloud platforms (AWS, GCP, Azure).
• Familiarity with MLOps tools like MLflow, Kubeflow, or Vertex AI for scalable ML pipelines.
• Excellent leadership, communication, and cross-functional collaboration skills.
• Bachelor’s or Master’s in Computer Science, Engineering, or related field (PhD preferred).

Nice to Have 

• Experience building Agentic applications 
• Experience training or fine-tuning foundation models.
• Contributions to open-source ML or LLM frameworks.
• Understanding of Responsible AI, bias mitigation, and model interpretability.

Perks of Freelancing With Turing:

• Work in a fully remote environment
• Opportunity to work on cutting-edge AI projects with leading LLM companies

Offer Details:

• Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST
• Employment type: Contractor assignment (no medical/paid leave)
• Duration of contract: 2 months; [expected start date is next week]
• Timezone : US PST ( 6 hours overlap required 12pm PST to 6pm PST) 

Evaluation Process (approximately 120 mins):

• Two rounds of interviews (60 min technical + 60 min technical & cultural discussion)