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About Turing: Job Title: Project Manager – Digital Transformation & AI SolutionsJob SummaryWe are looking for an experienced Project Manager with strong expertise in Digital Transformation, AI-driven solutions, and RPA implementations. The ideal candidate will lead end-to-end delivery of complex projects across global clients, ensuring execution within scope, timeline, and budget while driving measurable business outcomes.Key ResponsibilitiesLead end-to-end project lifecycle from use case identification to delivery and BAU transitionManage AI, RPA, and digital transformation projects in a global onsite-offshore modelDrive project governance, planning, execution, and stakeholder communicationDefine and track project scope, risks, issues, timelines, and budgetsCollaborate with business stakeholders to gather requirements and translate them into solutionsBuild business cases, ROI models, and solution proposalsManage cross-functional teams including business, technology, and operationsConduct steering committee meetings, project reviews, and status reportingIdentify process improvement and automation opportunities using AI/RPAEnsure resource planning and optimization across project phasesOversee documentation lifecycle (FDDs, process maps, SOPs, sign-offs) Support RFPs, due diligence, and go-to-market initiatives for digital solutionsRequired Skills & Experience 10+ years of experience in Project/Program Management or Digital Transformation Proven experience in: AI / Automation / RPA implementations Business Transformation initiatives Stakeholder & client management across geographies Strong expertise in: Project planning, risk & issue management Cost-benefit analysis and ROI tracking Agile/Scrum methodologies Hands-on experience with tools like:JIRA, Asana, MS Visio Ability to manage multiple concurrent projects and cross-functional teams Strong communication and consulting skillsPreferred Qualifications Certifications: Certified Scrum Master RPA (UiPath / Automation Anywhere) Azure Fundamentals (AZ-900)

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&LJob OverviewWe are looking for experienced engineers with deep design expertise to create challenging, simulation-based design problems for training and evaluating advanced AI models. The role focuses on crafting realistic engineering design tasks where a model must make genuine trade-offs, size components, and iterate against physics-based simulators to meet competing specifications.Key Responsibilities Design and validate simulation-based engineering problems that require true design reasoning, with clear constraints and optimization goals.  Deliver complete problem sets including reference solutions, near-miss variants, edge cases, and documentation, ensure appropriate difficulty with multiple failure modes, and collaborate with researchers to refine problems based on model performance.Domain TracksYou should have deep design expertise in at least one of the following; expertise spanning multiple tracks is a strong plus. Electrical & Computer Engineering — analog/mixed-signal IC design, power electronics, RF/microwave, digital system design, FPGA/ASIC, embedded systems. Mechanical Engineering — structural/thermal/fluid system design, mechanism design, HVAC, vibration/dynamics, manufacturing process design.Required Qualifications Master’s or PhD in a relevant engineering/applied science field. 3+ years of hands-on engineering design experience, producing validated designs from competing specs (not just analysis). Proficient in at least one open-source simulation tool relevant to the domain. Strong Python (or equivalent) scripting skills. High attention to detail across units, boundary conditions, convergence, and physical realism.Offer Details: Commitments Required: at least 4 hours per day and up to 40 hours per week with 4 hours of overlap with PST. Engagement type: ContractorEvaluation Process - Shortlisted candidates will be sent a Job Interest Form. After the profile review, an assessment will be shared, which must be completed within 24 hours. Based on the assessment outcomes, shortlisted candidates will be contacted to discuss the pre‑onboarding requirements.

About Turing: 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.Job Overview: We are seeking professionals with strong analytical and mathematical reasoning skills to create high-quality reasoning datasets for Large Language Model (LLM) training. This role focuses on designing and authoring complex, well-defined mathematical systems — including entirely new or fictional constructs — that require models to learn, reason, and prove properties from scratch.Ideal candidates possess a deep understanding of mathematical logic and formal systems (such as group theory, algebraic structures, or discrete mathematics) and can design tasks that assess whether models can apply newly defined axioms to perform calculations, derive properties, and construct valid proofs.Key Responsibilities: Design and define new mathematical objects and operations, similar to those in abstract algebra or group theory, but potentially fictional or modified (e.g., “Chromatic Numbers” where numbers have color attributes and custom addition rules). Author multi-part reasoning tasks that evaluate an LLM’s ability to interpret definitions, perform calculations, and prove properties within these newly defined systems. Develop problem types that include: Applying new mathematical rules to compute or simplify expressions. Proving or disproving structural properties (e.g., associativity, closure, commutativity). Performing symbolic manipulation within multi-layered or hybrid mathematical systems. Ensure every task includes: Deterministic answer(s) — solutions that can be verified against the defined system’s rules. Fully checked reasoning trace — step-by-step logical reasoning consistent with the provided definitions. A rubric that distinguishes between rule misuse, algebraic error, and incomplete proof, ensuring rigorous and consistent evaluation. Anticipate and handle corner cases such as color collisions, non-associative triples, undefined identities, or boundary-rule ambiguities. Collaborate with reviewers and LLM engineers to refine definitions and task phrasing, ensuring clarity, coherence, and reproducibility. Maintain quality and consistency standards across all tasks, emphasizing precision, completeness, and logical correctness.Qualifications: 2+ years of experience in a technical, mathematical, or analytical role (e.g., mathematics, computer science, logic, or data science). Strong background in abstract reasoning and familiarity with formal mathematical systems (group theory, modular arithmetic, symbolic logic, etc.). Proven ability to design structured reasoning problems that test both procedural understanding and conceptual application. Excellent written communication skills for creating clear, rigorous, and logically sound task descriptions and solutions. Demonstrated attention to detail and logical completeness, ensuring definitions and proofs remain internally consistent. Experience working with or evaluating Large Language Models (LLMs) is a plus. Background in Mathematics, Theoretical Computer Science, or a related STEM field preferredDeliverables: A structured collection of reasoning tasks covering: Definition and application of new mathematical systems. Proof and property reasoning. Complex expression evaluation and symbolic generalization. Each task must contain: A formal context block (system definition, axioms, and examples). A prompt query (calculation, proof, or reasoning challenge). An expected output (step-by-step reasoning trace leading to a deterministic final result). A rubric for scoring correctness, consistency, and completeness. Drafts must anticipate corner cases and demonstrate clear handling of exceptions or ambiguous scenarios. Final tasks must be self-contained, verifiable, and aligned with model reasoning evaluation goals. Offer Details: Commitments Required: Minimum 40 hours per week with overlap of 4 hours with PST.  Engagement  type  : Contractor assignment  Duration of contract : 5 weeksEvaluation Process - Shortlisted candidates will be sent a Job Interest Form. After the profile review, an assessment will be shared, which must be completed within 48 hours Based on the assessment outcomes, shortlisted candidates will be contacted to discuss the pre‑onboarding requirements

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 trajectories Offline 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 like Execute realistic coding tasks within the assigned agentic coding harness while maintaining model blindness and session independence Follow task instructions, milestones, planned interactions, and evaluation guardrails consistently across runs Verify model outputs by reading code, running commands, checking logs, and inspecting generated artifacts Perform targeted validation of outputs using tests, scripts, and manual checks Write clear, specific, evidence-based rationales for trajectory rankings and assessments Design multi-step, realistic coding tasks (offline work), including user intent and milestone structure Create and refine task-specific rubrics and binary evaluation criteria Review completed work for quality, completeness, consistency, and schema compliance Identify and escalate broken environments, unclear instructions, or process gaps with clear supporting evidenceRequirementsSoftware Engineering Fluency (Mandatory) 5+ years of experience in software engineering, QA, developer tooling, data/ML engineering, or similar code-heavy roles Strong 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 ecosystems Ability 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 correctAdditional Preferred Qualifications (Offline / Senior Candidates) Strong Docker skills and experience building/debugging reproducible environments Experience working in large, complex repositories (not just small or greenfield projects) Demonstrated originality and sound engineering judgment in defining technical problems Ability to design realistic, non-trivial tasks that go beyond tutorials, README flows, or simple bug fixesPerks of Freelancing With Turing Work on cutting-edge AI projects with leading foundation model companies Collaborate on high-impact work at the frontier of LLM evaluation and reasoning Remote, flexible opportunities with global teams Competitive compensation based on experience and project scopeOffer Details Commitments 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 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: Interacting with blinded models on predefined tasks, then ranking and grading the resulting trajectories Offline evaluations: Designing realistic coding tasks, calibrating them through user simulation, writing task-specific rubrics, and grading generated trajectoriesThis is not a basic annotation role. It requires strong engineering judgment, the ability to read and debug code, validate behavior, follow detailed process rules, and make consistent evaluation decisions across model runs.We are specifically looking for candidates with enough engineering maturity to independently handle real-world software tasks, not just toy problems or superficial code review exercises.What does day-to-day look like Execute realistic coding tasks within the assigned agentic coding harness while maintaining model blindness and session independence Follow task instructions, milestones, planned interactions, and evaluation guardrails consistently across runs Verify model outputs by reading code, running commands, checking logs, and validating generated artifacts Write clear, specific, evidence-based rationales for trajectory rankings and assessments Design multi-step, realistic coding tasks (offline work), including user intent, milestones, and expected behaviors Create and refine task-specific rubrics and binary evaluation criteria Review completed work for quality, consistency, completeness, and schema compliance Identify and escalate broken environments, unclear instructions, or process gaps with supporting evidenceRequirementsSoftware Engineering Fluency (Mandatory) 5+ years of experience in software engineering, QA, developer tooling, data/ML engineering, or similar code-heavy roles Strong hands-on experience in at least 1–2 programming languages or ecosystems Ability to:Read and understand unfamiliar codebasesRun and interpret tests, scripts, and CLI toolsDebug issues and reason about edge cases or partial fixesEvaluate whether an implementation is functionally correctRepresentative languages include:Python, JavaScript/TypeScript, Rust, Java, C/C++, Bash/CLI environments, Haskell, Swift, SQL, or other production-relevant ecosystemsTerminal & Tooling Skills (Mandatory) Comfortable working in Linux/Ubuntu-like environments Proficient with:Terminal workflowsGit basicsCode editors or IDEsPackage managers and test runnersJSON, YAML, and Markdown Familiarity with Docker and reproducible environments (strong plus, especially for offline work)Coding-Agent Workflow Familiarity (Mandatory) Comfortable working with or quickly adapting to agentic coding environments, such as:OpenCodeClaude CodeCursorSimilar coding-agent tools Ability to execute and evaluate tasks within agent-driven workflowsQuality Judgment & Annotation Accuracy (Mandatory) Ability to:Compare multiple model trajectories and identify meaningful differencesDistinguish correctness from style, communication quality, and agent behaviorEvaluate solutions consistently using defined rubricsFollow detailed process instructions without deviationMaintain consistency across repeated or similar evaluationsWrite concise, evidence-based rationales (not generic summaries)Work Style Highly detail-oriented and process-driven Comfortable with repetitive, high-precision evaluation work Able to maintain consistency across long tasks and multiple model runs Proactively flags ambiguity instead of making assumptions Balances realism with strict evaluation consistencyPerks of Freelancing With Turing Work on cutting-edge AI projects with leading foundation model companies Collaborate on high-impact work at the frontier of LLM evaluation and reasoning Remote, flexible opportunities with global teams Competitive compensation based on experience and project scopeOffer Details Commitments 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].