About Turing: About the projects: we are building LLM evaluation and training datasets to train LLM to work on realistic software engineering problems. One of our approaches, in this project, is to build verifiable SWE tasks based on public repository histories in a synthetic approach with human-in-the-loop; while expanding the dataset coverage to different types of tasks in terms of programming language, difficulty level, and etc.About the Role: We are looking for experienced software engineers (tech lead level) who are familiar with high-quality public GitHub repositories and can contribute to this project. This role involves hands-on software engineering work, including development environment automation, issue triaging, and evaluating test coverage and qualityWhy Join Us? Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. You’ll be at the forefront of evaluating how LLMs interact with real code, influencing the future of AI-assisted software development. This is a unique opportunity to blend practical software engineering with AI research.What does day-to-day look like: Analyze and triage GitHub issues across trending open-source libraries. Set up and configure code repositories, including Dockerization and environment setup. Evaluating unit test coverage and quality. Modify and run codebases locally to assess LLM performance in bug-fixing scenarios. Collaborate with researchers to design and identify repositories and issues that are challenging for LLMs. Opportunities to lead a team of junior engineers to collaborate on projects.Required Skills: Minimum 3+ years of overall experience Strong experience with at least one of the following languages: C# Proficiency with Git, Docker, and basic software pipeline setup. Ability to understand and navigate complex codebases. Comfortable running, modifying, and testing real-world projects locally. Experience contributing to or evaluating open-source projects is a plus.Nice to Have: Previous participation in LLM research or evaluation projects. Experience building or testing developer tools or automation agents.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. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week) Employment type : Contractor assignment (no medical/paid leave) Location : India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, MexicoEvaluation Process (approximately 75 mins) : Two rounds of interviews (60 min technical + 30 min technical & cultural discussion)
About Turing: Senior LLM Engineer – GenAI / ML (Python, Langchain)Full TimeLocation: IndiaOverall Experience: 7–12 YearsFocus: Hands-on engineering role focused on designing, building, and deploying Generative AI and LLM-based solutions. The role requires deep technical proficiency in Python and modern LLM frameworks with the ability to contribute to roadmap development and cross-functional collaboration.Key Responsibilities: Design and develop GenAI/LLM-based systems using tools such as Langchain and Retrieval-Augmented Generation (RAG) pipelines. Implement prompt engineering techniques and agent-based frameworks to deliver intelligent, context-aware solutions. Collaborate with the engineering team to shape and drive the technical roadmap for LLM initiatives. Translate business needs into scalable, production-ready AI solutions. Work closely with business SMEs and data teams to ensure alignment of AI models with real-world use cases. Contribute to architecture discussions, code reviews, and performance optimization.Skills Required: Proficient in Python, Langchain, and SQL. Understanding of LLM internals, including prompt tuning, embeddings, vector databases, and agent workflows. Background in machine learning or software engineering with a focus on system-level thinking. Experience working with cloud platforms like AWS, Azure, or GCP. Ability to work independently while collaborating effectively across teams. Excellent communication and stakeholder management skills.Preferred Qualifications: 1+ years of hands-on experience in LLMs and Generative AI techniques. Experience contributing to ML/AI product pipelines or end-to-end deployments. Familiarity with MLOps and scalable deployment patterns for AI models. Prior exposure to client-facing projects or cross-functional AI teams.
Machine Learning
Artificial Intelligence
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&LRole 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, JavaScript (including ReactJS), C/C++, Java, Rust, and Go; evaluating and refining AI-generated code for efficiency, scalability, and reliability; and working with cross-functional teams to enhance enterprise-level AI-driven coding solutions.What does day-to-day life look like? Working on AI model training initiatives by curating code examples, building solutions, and correcting code in Python, 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 that can verify the quality of the code and identify error patterns. Hypothetize on steps in the software engineering cycle (prototyping, architecture design, API design, production implementation, launch, experiments, monitoring, operation maintenance) and evaluate model capabilities on them Design verification mechanisms that can automatically verify a solution to a software engineering task.Requirements Several years of software engineering experience, including 2+ years of continuous full-time experience at a top-tier product company (e.g., Google, Stripe, Amazon, Apple, Meta, Netflix, Microsoft, Datadog, Dropbox, Shopify, PayPal, IBM Research). Strong expertise in building full-stack applications 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.Offer Details Commitment: flexible engagement, minimum 10 hrs/week, up to 40 hrs/week (partial PST overlap required) Type: Contractor (no medical/paid leave) Duration:1 month (starting next week; potential extensions based on performance and fit)
About Micro1: Join our team as a Software AI Engineer and play a pivotal role in driving mission-critical government initiatives while also contributing to micro1’s proprietary AI infrastructure. This position offers the unique opportunity to work at the intersection of applied AI research and high-impact, production-grade deployment, leveraging the latest in LLMs, RAG, and multi-agent systems. Key ResponsibilitiesDesign, build, and deploy advanced AI/ML solutions for government clients, ensuring robust and secure implementation at scale.Collaborate with internal and external teams to architect and enhance AI-driven platforms, focusing on RAG, LLM orchestration, and multi-agent workflows.Develop and maintain APIs, SDK integrations, and scalable pipelines, utilizing Python and RESTful best practices.Leverage cloud platforms such as AWS GovCloud, Vertex AI, and AWS Bedrock to deliver secure, enterprise-grade solutions.Implement data ontologies, metadata catalogs, and ETL pipelines to support advanced AI and analytics use cases.Apply best practices in prompt engineering, LangGraph/LangChain, and tool integration for agentic AI systems.Ensure clear, concise, and effective written and verbal communication across all collaborative efforts.
About Micro1: Join our team as a AI/ML Engineer and play a pivotal role in driving mission-critical government initiatives while also contributing to micro1’s proprietary AI infrastructure, you’ll harness advanced large language models (LLMs), retrieval-augmented generation (RAG), and multi-agent orchestration to deliver secure, scalable, and impactful machine learning systems. You’ll work closely with cross-functional experts, leveraging frontier AI platforms and the latest in agentic AI tooling. Key Responsibilities:Design, implement, and optimize AI/ML models particularly leveraging LLMs, RAG, and prompt engineering for production grade applications.Develop and orchestrate multi-agent systems using frameworks such as LangGraph and LangChain.Integrate and deploy solutions on secure cloud environments, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.Build robust data pipelines, manage ETL processes, and develop metadata catalogs and ontologies to ensure high-quality data for AI training and inference.Create and maintain REST APIs and SDK integrations to facilitate seamless data and model interactions.Collaborate with product, security, and engineering teams to ensure best-in-class delivery, following secure coding and DevOps best practices (CI/CD).Document technical decisions and communicate complex concepts clearly to both technical and non-technical stakeholders.
