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fetchjobs.co
Job details:
About The Company
Turing, headquartered in San Francisco, California, is recognized as the world's leading research accelerator for frontier artificial intelligence labs. The company serves as a trusted partner for global enterprises deploying advanced AI systems, supporting them through innovative research and development initiatives. Turing's core mission is to accelerate frontier research by providing high-quality data, sophisticated training pipelines, and access to top-tier AI researchers specializing in coding, reasoning, STEM disciplines, multilinguality, multimodality, and agent-based systems. Additionally, Turing leverages its expertise to help enterprises convert AI proof-of-concept models into proprietary, reliable, and impactful systems that deliver measurable results and enhance profitability. The company's commitment to pushing the boundaries of AI innovation makes it a pivotal player in the AI research ecosystem, fostering advancements that shape the future of technology and industry applications.
About The Role
We are seeking experienced Data Analysts specializing as Machine Learning Evaluation (MLE) Bench to join our dynamic team. This role is pivotal in conducting benchmark-driven evaluation projects focused on real-world machine learning systems. The successful candidate will engage in hands-on analytical work involving production-like datasets, metrics, and ML outputs to assess, diagnose, and enhance the performance of cutting-edge AI models. The role requires a blend of data analysis expertise and a solid understanding of machine learning workflows, enabling the analyst to identify performance bottlenecks, failure modes, and edge cases that are critical for refining AI systems. The ideal candidate will be proactive, detail-oriented, and capable of working collaboratively with ML engineers and researchers to develop challenging evaluation scenarios that mirror real-world complexities. This position offers a unique opportunity to contribute directly to the advancement of AI technology at the forefront of research and deployment.
Qualifications
The ideal candidate will possess a minimum of three years of professional experience as a Data Analyst or an analytics-focused engineer. Proficiency in Python is essential for data analysis, along with solid experience in SQL for managing and querying relational datasets. A strong understanding of statistics and analytical reasoning is required to interpret ML outputs and evaluation metrics accurately. Candidates should have demonstrated experience working with large, complex datasets and extracting reliable insights. Excellent communication skills in English—both spoken and written—are necessary to effectively collaborate with cross-functional teams and document analytical findings. Familiarity with analyzing ML models, understanding evaluation metrics, and diagnosing model performance issues will be highly advantageous. Candidates should also be adept at writing clean, well-documented, and reproducible analytical code to ensure transparency and reproducibility of their work.
Responsibilities
- Analyze structured and unstructured datasets generated from machine learning training, inference, and evaluation pipelines to derive meaningful insights.
- Define, compute, and validate performance metrics used to evaluate model behavior and effectiveness across various benchmarks.
- Investigate data distributions, model outputs, failure modes, and edge cases relevant to benchmark tasks to identify areas for improvement.
- Develop and execute Python and SQL scripts to analyze data, generate reports, and support ongoing evaluation workflows.
- Ensure data quality, consistency, and correctness across datasets and experimental results through rigorous validation processes.
- Create clear, comprehensive, and well-documented analytical artifacts, including reports and reproducible workflows, to facilitate team understanding and future reference.
- Collaborate closely with ML engineers and researchers to design challenging, real-world evaluation scenarios that accurately reflect deployment conditions and performance expectations.
Benefits
Joining Turing as a freelancer offers the flexibility of working in a fully remote environment, allowing you to balance your professional and personal commitments effectively. You will have the opportunity to work on cutting-edge AI projects alongside leading LLM companies, gaining exposure to the latest advancements in AI research and deployment. Turing provides a platform for talented professionals to contribute to impactful projects that shape the future of AI technology, while also expanding their skills and professional network. The engagement offers flexibility in terms of working hours, with a minimum commitment of four hours per day and at least 20 hours per week, ensuring a manageable workload that aligns with your availability.
Equal Opportunity
Turing is an equal opportunity employer committed to fostering an inclusive environment for all employees and contractors. We value diversity and are dedicated to providing equal employment opportunities regardless of race, ethnicity, gender, age, sexual orientation, disability, or any other protected characteristic. We believe that diverse perspectives and experiences drive innovation and excellence, and we strive to create a workplace where everyone feels valued, respected, and empowered to contribute their best work.
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