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About Turing: About TuringBased 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 OverviewWe are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems.The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments. What does day-to-day life look like?Work with real-world ML codebases to support MLE Bench–style evaluation tasks.Build, run, and modify model training, evaluation, and inference pipelines.Prepare datasets, features, and metrics for ML benchmarking and validation.Debug, refactor, and improve production-like ML systems for correctness and performance.Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks.Write clean, reproducible, and well-documented Python code for ML workflows.Participate in code reviews to ensure high standards of engineering quality.Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.RequirementsMinimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused).Strong proficiency in Python for machine learning and data workflows.Hands-on experience with model training, evaluation, and inference pipelines.Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization).Experience working with ML frameworks (e.g., PyTorch, TensorFlow, JAX, or similar).Ability to understand, navigate, and modify complex, real-world ML codebases.Experience writing readable, reusable, and maintainable production-quality code.Strong problem-solving and debugging skills.Excellent spoken and written English communication skills.Perks of Freelancing With TuringWork in a fully remote environment.Opportunity to work on cutting-edge AI projects with leading LLM companies.Offer DetailsCommitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST.Engagement Type: Contractor assignment (no medical/paid leave)Duration of Contract: 3 months (adjustable based on engagement)Location: India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Brazil, MexicoEvaluation ProcessTechnical Interview with live coding challege (60 mins)

About Turing: About TuringTuring 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 OverviewWe are looking for strong, detail-oriented software practitioners to help evaluate and improve datasets for agentic coding models.This role involves working with realistic coding tasks in an agentic coding harness, reviewing model trajectories, verifying solutions, and producing high-quality annotations.Depending on the assignment, the work may include:Online evaluations: Manually interacting with blinded models on predefined tasks, then ranking and grading resulting trajectoriesOffline evaluations: Designing realistic coding tasks, calibrating them through user simulation, writing task-specific rubrics, and grading generated trajectoriesThis is not a basic annotation role. Candidates are expected to read and debug code, validate behavior, follow detailed process rules, and make consistent judgment calls across model runs.We are specifically looking for candidates with enough engineering maturity to independently work on realistic software tasks, not just toy problems or shallow code-review exercises. What does day-to-day look likeExecute realistic coding tasks within the assigned agentic coding harness while maintaining model blindness and session independenceFollow task instructions, milestones, planned interactions, and evaluation guardrails consistently across runsVerify model outputs by reading code, running commands, checking logs, and inspecting generated artifactsPerform targeted validation of outputs using tests, scripts, and manual checksWrite clear, specific, evidence-based rationales for trajectory rankings and assessmentsDesign multi-step, realistic coding tasks (offline work), including user intent and milestone structureCreate and refine task-specific rubrics and binary evaluation criteriaReview completed work for quality, completeness, consistency, and schema complianceIdentify and escalate broken environments, unclear instructions, or process gaps with clear supporting evidenceRequirements Software Engineering Fluency (Mandatory)5+ years of experience in software engineering, QA, developer tooling, data/ML engineering, or similar code-heavy rolesStrong hands-on experience in at least 1–2 programming languages or ecosystemsRepresentative languages include :Python, JavaScript/TypeScript, Rust, Java, C/C++, Bash/CLI environments, Haskell, Swift, SQL, or other production-relevant ecosystemsAbility to: Read and understand unfamiliar codebases Run and interpret tests, scripts, and CLI tools Debug issues and reason about edge cases or partial fixes Evaluate whether an implementation is functionally correct Additional Preferred Qualifications (Offline / Senior Candidates)Strong Docker skills and experience building/debugging reproducible environmentsExperience working in large, complex repositories (not just small or greenfield projects)Demonstrated originality and sound engineering judgment in defining technical problemsAbility to design realistic, non-trivial tasks that go beyond tutorials, README flows, or simple bug fixesPerks of Freelancing With TuringWork on cutting-edge AI projects with leading foundation model companiesCollaborate on high-impact work at the frontier of LLM evaluation and reasoningRemote, flexible opportunities with global teamsCompetitive compensation based on experience and project scopeOffer DetailsCommitments Required: 8 hours per day with a 4-hour overlap with PST.Employment Type: Contractor position (Note: this role does not include medical/paid leave).Duration of Contract: 5 weeks; [expected start date is next week].

About Turing: About UsBased 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 software engineering, logical 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.Ideal BackgroundThis role is ideal for engineers who have worked at the frontier of AI — at companies like OpenAI, NVIDIA, Databricks, Palantir, Snowflake, or similar organizations pushing the boundaries of intelligent systems. We especially welcome graduates from programs with strong CS foundations such as University of Washington, University of Illinois Urbana-Champaign, UT Austin, University of Michigan, Purdue, and comparable institutions — though exceptional experience and skill always take precedence over pedigree.Project OverviewAs a Software Engineering evaluator, you will create cutting-edge datasets for training, benchmarking, and advancing large language models, collaborating closely with researchers. This includes curating code examples, providing precise solutions, and making corrections — with a primary focus on Python across backend services, data pipelines, and ML infrastructure, alongside JavaScript (including ReactJS), C/C++, Java, Rust, and Go. You will evaluate and refine AI-generated code for efficiency, scalability, and reliability, and work with cross-functional teams to enhance enterprise-level AI-driven coding solutions.What Does a Typical Day Look Like? Work on AI model training initiatives by curating code examples, building solutions, and correcting code — primarily in Python, with additional work in JavaScript (including ReactJS), C/C++, Java, Rust, and Go. Evaluate and refine AI-generated code to ensure that it is efficient, scalable, and reliable. Collaborate with cross-functional teams to enhance AI-driven coding solutions against industry performance benchmarks. Build agents and automated verification tools in Python that can verify the quality of code and identify error patterns. Hypothesize on steps in the software engineering cycle (prototyping, architecture design, API design, production implementation, launch, experiments, monitoring, operational maintenance) and evaluate model capabilities on them. Design verification mechanisms that can automatically verify a solution to a software engineering task.Required Skills Several years of software engineering experience (3 years or more) Strong expertise in Python with deep knowledge of frameworks, tooling, and best practices for building production-grade software. Experience building full-stack applications and deploying scalable software using modern languages and tools. Deep understanding of software architecture, design, development, debugging, and code quality/review assessment. Excellent oral and written communication skills for clear, structured evaluation rationales.Engagement Details Commitment: flexible engagement, minimum 10 hrs/week, up to 40 hrs/week Type: Contractor (no medical/paid leave) Duration: 1 month (potential extensions based on performance and fit) Location: Candidates must be based in the United StatesEvaluation Process The application process takes 15–30 minutes. Completion of an AI video interview is required.

About Turing: About UsBased 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 software engineering, logical 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.Ideal BackgroundThis role is ideal for engineers who have shipped high-impact products at fast-moving companies like Stripe, Airbnb, Cloudflare, Datadog, Coinbase, or similar high-growth engineering environments. We especially welcome graduates from top computer science programs such as Stanford, MIT, Carnegie Mellon, UC Berkeley, Georgia Tech, and comparable institutions — though exceptional experience and skill always take precedence over pedigree.Project OverviewAs a Software Engineering evaluator, you will create cutting-edge datasets for training, benchmarking, and advancing large language models, collaborating closely with researchers. This includes curating code examples, providing precise solutions, and making corrections in Python, C/C++, Rust, Go, Java, and JavaScript (including ReactJS) — with particular emphasis on systems-level code, performance-critical applications, and infrastructure. You will evaluate and refine AI-generated code for efficiency, scalability, and reliability, and work with cross-functional teams to enhance enterprise-level AI-driven coding solutions.What Does a Typical Day Look Like? Work on AI model training initiatives by curating code examples, building solutions, and correcting code in Python, C/C++, Rust, Go, Java, and JavaScript (including ReactJS). Evaluate and refine AI-generated code with an emphasis on systems-level correctness, performance, and reliability. Collaborate with cross-functional teams to enhance AI-driven coding solutions against industry performance benchmarks. Build agents that can verify the quality of systems-level and infrastructure code and identify error patterns. Hypothesize on steps in the software engineering cycle (prototyping, architecture design, API design, production implementation, launch, experiments, monitoring, operational maintenance) and evaluate model capabilities on them. Design verification mechanisms that can automatically verify a solution to a software engineering task.Required Skills Several years of software engineering experience (3 years or more) Strong expertise in systems programming, infrastructure, or backend development using languages like Python, C/C++, Rust, and Go. Experience building and deploying scalable, production-grade software using modern languages and tools. Deep understanding of software architecture, design, development, debugging, and code quality/review assessment. Excellent oral and written communication skills for clear, structured evaluation rationales.Engagement Details Commitment: flexible engagement, minimum 10 hrs/week, up to 40 hrs/week Type: Contractor (no medical/paid leave) Duration: 1 month (potential extensions based on performance and fit) Location: Candidates must be based in the United StatesEvaluation Process The application process takes 15–30 minutes. Completion of an AI video interview is required.

About Turing: About UsBased 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 software engineering, logical 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.Ideal BackgroundThis role is ideal for engineers who have shipped high-impact products at fast-moving companies like Stripe, Airbnb, Cloudflare, Datadog, Coinbase, or similar high-growth engineering environments. We especially welcome graduates from leading programs such as Harvard, Columbia, Princeton, Yale, University of Pennsylvania, and comparable institutions — though exceptional experience and skill always take precedence over pedigree.Project OverviewAs a Software Engineering evaluator, you will create cutting-edge datasets for training, benchmarking, and advancing large language models, collaborating closely with researchers. This includes curating code examples, providing precise solutions, and making corrections — with a primary focus on Python across backend services, data pipelines, and ML infrastructure, alongside JavaScript (including ReactJS), C/C++, Java, Rust, and Go. You will evaluate and refine AI-generated code for efficiency, scalability, and reliability, and work with cross-functional teams to enhance enterprise-level AI-driven coding solutions.What Does a Typical Day Look Like? Work on AI model training initiatives by curating code examples, building solutions, and correcting code — primarily in Python, with additional work in JavaScript (including ReactJS), C/C++, Java, Rust, and Go. Evaluate and refine AI-generated code to ensure that it is efficient, scalable, and reliable. Collaborate with cross-functional teams to enhance AI-driven coding solutions against industry performance benchmarks. Build agents and automated verification tools in Python that can verify the quality of code and identify error patterns. Hypothesize on steps in the software engineering cycle (prototyping, architecture design, API design, production implementation, launch, experiments, monitoring, operational maintenance) and evaluate model capabilities on them. Design verification mechanisms that can automatically verify a solution to a software engineering task.Required Skills Several years of software engineering experience (3 years or more) Strong expertise in Python with deep knowledge of frameworks, tooling, and best practices for building production-grade software. Experience building full-stack applications and deploying scalable software using modern languages and tools. Deep understanding of software architecture, design, development, debugging, and code quality/review assessment. Excellent oral and written communication skills for clear, structured evaluation rationales.Engagement Details Commitment: flexible engagement, minimum 10 hrs/week, up to 40 hrs/week Type: Contractor (no medical/paid leave) Duration: 1 month (potential extensions based on performance and fit) Location: Candidates must be based in the United StatesEvaluation Process The application process takes 15–30 minutes. Completion of an AI video interview is required.