Website:
agilegridsolution.com
Job details:
About The Company
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 its clients in two primary ways: by accelerating frontier research through high-quality data, sophisticated training pipelines, and top-tier AI researchers specializing in coding, reasoning, STEM, multilinguality, multimodality, and agents; and by applying this expertise to help enterprises transform AI from proof of concept into proprietary intelligence. Our systems are designed to perform reliably, deliver measurable impact, and generate lasting results on the bottom line. Turing’s innovative approach positions it at the forefront of AI development, fostering breakthroughs that shape the future of technology and enterprise AI solutions.
About The Role
We are seeking experienced Machine Learning Engineers (MLE Bench) to join our dynamic team. In this role, you will focus on benchmark-driven evaluation projects centered on real-world machine learning systems. Your core responsibilities will involve working hands-on with production-grade ML codebases, developing and refining model training and evaluation pipelines, and supporting deployment workflows. The primary goal is to assess and enhance the capabilities of advanced AI models, ensuring they meet rigorous standards of performance and reliability. The successful candidate will act as a bridge between research and engineering, engaging deeply with models, data, and infrastructure within realistic ML environments. This position offers an exciting opportunity to contribute to cutting-edge AI evaluation efforts that directly impact enterprise AI deployment and advancement.
Qualifications
The ideal candidate will possess a minimum of 3+ years of experience as a Machine Learning Engineer or Software Engineer with a focus on ML. They should demonstrate strong proficiency in Python, particularly for machine learning and data workflows. Hands-on experience with model training, evaluation, and inference pipelines is essential. Candidates should have a solid understanding of fundamental machine learning concepts, including supervised and unsupervised learning, evaluation metrics, and optimization techniques. Experience working with popular ML frameworks such as PyTorch, TensorFlow, or JAX is required. Additionally, candidates must be capable of navigating and modifying complex, real-world ML codebases and writing clean, reusable, and maintainable production-quality code. Excellent problem-solving skills, debugging capabilities, and strong communication skills in English are also crucial for success in this role.
Responsibilities
Your day-to-day responsibilities will include working with real-world ML codebases to support evaluation tasks aligned with MLE Bench standards. You will build, run, and modify model training, evaluation, and inference pipelines to ensure robustness and efficiency. Preparing datasets, features, and metrics for benchmarking and validation will be a key part of your role. You will debug, refactor, and optimize production-like ML systems to improve correctness and performance. Additionally, you will evaluate model behavior, identify failure modes, and analyze edge cases relevant to benchmark tasks. Writing clean, well-documented Python code for ML workflows is essential, as is participating in code reviews to uphold high engineering standards. Collaboration with researchers and engineers will be vital in designing challenging, real-world ML engineering tasks for comprehensive AI system evaluation.
Benefits
As a freelancer working with Turing, you will enjoy the flexibility of a fully remote work environment, allowing you to work from anywhere. You will have the opportunity to engage in cutting-edge AI projects alongside leading LLM companies, enhancing your skills and industry knowledge. Turing offers a flexible engagement model with a commitment of at least 4 hours per day and a minimum of 20 hours per week, with a required overlap of 4 hours with PST. The initial contract duration is three months, with potential for extension based on performance and project needs. Additionally, freelancers can benefit from a referral program, earning rewards by recommending talented professionals in their network.
Equal Opportunity
Turing is committed to creating an inclusive environment where all employees and freelancers are valued and respected. We are an equal opportunity employer and do not discriminate based on race, color, religion, gender, sexual orientation, national origin, age, disability, or any other protected status. We believe diversity enhances our innovation and success, and we strive to foster a workplace culture that promotes fairness, equity, and opportunity for all.
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