Senior ML Engineer at Ktek Resourcing | Torre

Senior ML Engineer

Freelance
Recurrent (~15 hours per week)
Compensation
USD60 - 120/hour
Negotiable
location_on
Remote (anywhere)
Posted about 18 hours ago

Responsibilities


Role: Senior ML Engineer (MSc. or PhD). Location: Global, fully remote. Job Type: Contractor (~15 hours per week). Schedule: Flexible-you choose the hours and days you work, including weekends if desired. Geographic Eligibility: NAMER, LATAM, Europe, South Korea, Japan, Bangladesh, Egypt, Singapore and Lithuania. Project Overview: - We are looking for highly skilled Machine Learning Experts to contribute to an AI training project involving model development, training and inference systems, numerical computing, performance optimization, and Python. - The work involves creating, solving, reviewing, and validating challenging machine-learning engineering tasks. - A representative task may require implementing or modifying a model, constructing a reproducible training or inference workflow, optimizing memory or throughput, debugging numerical or system-level failures, and verifying that the resulting implementation satisfies objective correctness and performance requirements. - This is a very coding heavy role. - Candidates must have experience using coding agents with Python in their workflow. What You’ll Work On: - Develop and validate machine-learning models, training pipelines, inference systems, and supporting infrastructure. - Implement model components, data pipelines, evaluation systems, and numerical methods. - Build reproducible programmatic workflows using Python and command-line tools. Required Qualifications: - A master’s degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline. - Strong professional or research experience in machine learning. - Practical proficiency with Python and coding agents. - Equivalent tools may also be considered when the candidate demonstrates directly relevant depth. - Experience at a well-established technology company, AI laboratory, research organization, or other recognized engineering environment is strongly preferred. - Exceptional open-source or academic experience may also qualify.
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