108 jobs found

Job Description About Us: 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 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 Background: This role is ideal for engineers who have built production systems at companies like Google, Microsoft, Apple, Amazon, Meta, or similar high-scale engineering organizations. 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 Overview: As 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 States Evaluation Process: The application process takes 15-30 minutes. Completion of an AI video interview is required.

Job Description About Us: 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 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 Background: This role is ideal for engineers who have built production systems at companies like Google, Microsoft, Apple, Amazon, Meta, or similar high-scale engineering organizations. 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 Overview: As 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 States Evaluation Process: The application process takes 15-30 minutes. Completion of an AI video interview is required.

Job Description About Us: 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 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 Background: This role is ideal for engineers who have built production systems at companies like Google, Microsoft, Apple, Amazon, Meta, or similar high-scale engineering organizations. 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 Overview: As 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 States Evaluation Process: The application process takes 15-30 minutes. Completion of an AI video interview is required.

Job Description About Us: 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 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 Background: This role is ideal for engineers who have built production systems at companies like Google, Microsoft, Apple, Amazon, Meta, or similar high-scale engineering organizations. 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 Overview: As 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 States Evaluation Process: The application process takes 15-30 minutes. Completion of an AI video interview is required.

Job Description About Us: 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 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 Background: This role is ideal for engineers who have built production systems at companies like Google, Microsoft, Apple, Amazon, Meta, or similar high-scale engineering organizations. 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 Overview: As 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 States Evaluation Process: The application process takes 15-30 minutes. Completion of an AI video interview is required.

Job Description About Us: 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 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 Background: This role is ideal for engineers who have built production systems at companies like Google, Microsoft, Apple, Amazon, Meta, or similar high-scale engineering organizations. 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 Overview: As 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 States Evaluation Process: The application process takes 15-30 minutes. Completion of an AI video interview is required.

Job Description About Us: 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 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 Background: This role is ideal for engineers who have built production systems at companies like Google, Microsoft, Apple, Amazon, Meta, or similar high-scale engineering organizations. 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 Overview: As 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 States Evaluation Process: The application process takes 15-30 minutes. Completion of an AI video interview is required.

Job Description About Us: 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 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 Background: This role is ideal for engineers who have built production systems at companies like Google, Microsoft, Apple, Amazon, Meta, or similar high-scale engineering organizations. 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 Overview: As 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 States Evaluation Process: The application process takes 15-30 minutes. Completion of an AI video interview is required.

Job Description About Us: 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 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 Background: This role is ideal for engineers who have built production systems at companies like Google, Microsoft, Apple, Amazon, Meta, or similar high-scale engineering organizations. 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 Overview: As 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 States Evaluation Process: The application process takes 15-30 minutes. Completion of an AI video interview is required.

Job Description About Us: 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 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 Background: This role is ideal for engineers who have built production systems at companies like Google, Microsoft, Apple, Amazon, Meta, or similar high-scale engineering organizations. 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 Overview: As 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 States Evaluation Process: The application process takes 15-30 minutes. Completion of an AI video interview is required.

Job Description About Us: 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 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 Background: This role is ideal for engineers who have built production systems at companies like Google, Microsoft, Apple, Amazon, Meta, or similar high-scale engineering organizations. 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 Overview: As 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 States Evaluation Process: The application process takes 15-30 minutes. Completion of an AI video interview is required.

Job Description About Us: 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 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 Background: This role is ideal for engineers who have built production systems at companies like Google, Microsoft, Apple, Amazon, Meta, or similar high-scale engineering organizations. 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 Overview: As 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 States Evaluation Process: The application process takes 15-30 minutes. Completion of an AI video interview is required.

Job Description About Us: 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 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 Background: This role is ideal for engineers who have built production systems at companies like Google, Microsoft, Apple, Amazon, Meta, or similar high-scale engineering organizations. 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 Overview: As 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 States Evaluation Process: The application process takes 15-30 minutes. Completion of an AI video interview is required.

Job Description Require Only W2 and Local Candidates, F2F Interview Hi, This is Amit Kumar Srivastava from AppLab Systems, my client is looking for Azure DevOps Lead Technical Consultant - Charlotte, NC(Onsite). Please go through the requirement and let me know your interest. Job- DevOps Lead Technical Consultant Location: Charlotte, NC (Onsite) Duration- 1 Year Face to face interview is must, Need Local Candidate Role Overview We are seeking an experienced Senior DevOps / Release Automation Engineer to design, develop, and maintain enterprise-grade CI/CD platforms, deployment automation frameworks, and release orchestration solutions. The ideal candidate is a hands-on engineer who has built automation using Python, Jenkins, Ansible, JFrog Artifactory, and Git-based workflows in highly regulated environments with formal release governance. This is not a cloud infrastructure engineering role focused primarily on Terraform, networking, VPCs, or infrastructure provisioning. The primary focus is release automation, software delivery lifecycle management, artifact promotion, and deployment platform engineering. Key Responsibilities CI/CD Pipeline Engineering • Design and develop CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI/CD, Harness, or equivalent platforms. • Create pipeline-as-code solutions with conditional logic based on Git branches, tags, release types, and deployment targets. • Implement reusable deployment workflows that support multiple application teams. Release Automation • Design and maintain automated release processes across DEV, SIT, UAT, and PROD environments. • Implement approval gates, artifact promotion workflows, and deployment controls. • Standardize deployments across multiple applications and business units. Ansible Automation • Develop Ansible playbooks from scratch. • Design reusable Ansible roles and Jinja2 templates. • Manage environment-specific configurations and inventory structures. • Develop Ansible Tower/AWX workflows, surveys, and role-based deployment processes. Python Development • Develop Python automation solutions for: o File processing o YAML/JSON/XML parsing o Regex-based routing logic o Command execution using subprocess o Release orchestration o Build automation o Configuration management Artifact Management • Administer JFrog Artifactory repositories. • Implement artifact publishing and promotion workflows. • Design environment-specific artifact lifecycle management. Source Control Management • Manage Git workflows including: o Branching strategies o Cherry-picking o Merge conflict resolution o Release branching o Tag management o Git LFS Database Release Management • Build and maintain Liquibase-based database deployment pipelines. • Create changelogs, changesets, rollback strategies, and context-based deployments. Enterprise Governance • Work within regulated release management frameworks. • Support change approvals and CAB processes. • Ensure auditability, traceability, and compliance requirements are met. Required Qualifications • 10+ years of DevOps, CI/CD, Release Engineering, or Release Automation experience. • Advanced Python scripting experience. • Strong Jenkins Pipeline (Jenkinsfile/Groovy) development experience. • Strong Ansible and Ansible Tower/AWX experience. • Hands-on JFrog Artifactory experience. • Strong Git expertise beyond basic source control usage. • Experience with Liquibase or comparable database release tooling. • Experience supporting enterprise SDLC and release governance processes. • Experience building automation solutions for consumption by multiple engineering teams. Preferred Qualifications • Payment's domain experience: o ACI o Volante o FIS o Fedwire o CHIPS o SWIFT o ISO 20022 • Financial services experience: o Wells Fargo o JPMorgan Chase o Bank of America o Citi o Capital One • Experience in highly regulated enterprise environments.

Job Description About Us: 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 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 Background: This role is ideal for engineers who have built production systems at companies like Google, Microsoft, Apple, Amazon, Meta, or similar high-scale engineering organizations. 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 Overview: As 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 States Evaluation Process: The application process takes 15-30 minutes. Completion of an AI video interview is required.

Job Description About Us: 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 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 Background: This role is ideal for engineers who have built production systems at companies like Google, Microsoft, Apple, Amazon, Meta, or similar high-scale engineering organizations. 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 Overview: As 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 States Evaluation Process: The application process takes 15-30 minutes. Completion of an AI video interview is required.

Job Description About Us: 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 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 Background: This role is ideal for engineers who have built production systems at companies like Google, Microsoft, Apple, Amazon, Meta, or similar high-scale engineering organizations. 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 Overview: As 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 States Evaluation Process: The application process takes 15-30 minutes. Completion of an AI video interview is required.

Job Description About Us: 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 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 Background: This role is ideal for engineers who have built production systems at companies like Google, Microsoft, Apple, Amazon, Meta, or similar high-scale engineering organizations. 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 Overview: As 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 States Evaluation Process: The application process takes 15-30 minutes. Completion of an AI video interview is required.

Job Description About Us: 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 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 Background: This role is ideal for engineers who have built production systems at companies like Google, Microsoft, Apple, Amazon, Meta, or similar high-scale engineering organizations. 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 Overview: As 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 States Evaluation Process: The application process takes 15-30 minutes. Completion of an AI video interview is required.

Job Description About Us: 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 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 Background: This role is ideal for engineers who have built production systems at companies like Google, Microsoft, Apple, Amazon, Meta, or similar high-scale engineering organizations. 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 Overview: As 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 States Evaluation Process: The application process takes 15-30 minutes. Completion of an AI video interview is required.