Openkyber
Machine Learning Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer on a W2 contract for over 6 months, offering $114,400 - $135,200 per year. Located remotely, it requires strong Python and PyTorch skills, experience with ML infrastructure, and debugging complex systems.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
614
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🗓️ - Date
February 25, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Remote
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
Alaska
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🧠 - Skills detailed
#Scala #Debugging #PyTorch #Python #ML (Machine Learning) #AI (Artificial Intelligence)
Role description
Backend Software Engineer: Python-PyTorch W2 Contract Salary Range: $114,400 - $135,200 per year Location: Cupertino, CA - Remote Role
Job Summary: We are seeking experienced AI / ML Infrastructure Engineers to join a central ML/AI platform team responsible for building foundational services used by multiple internal and external product organizations. This role focuses on designing, extending, and supporting scalable ML infrastructure that powers both traditional machine learning and modern LLM-based workflows.
Duties and Responsibilities: Design, develop, and enhance ML infrastructure services supporting training, inference, experimentation, and embeddings lifecycle management. Implement small to medium-sized features across existing ML platform components. Take customer use cases end-to-end, including investigation, debugging, and resolution of issues. Work across the ML stack, collaborating closely with applied scientists and downstream product teams. Diagnose and resolve issues in production ML systems. Navigate ambiguous requirements and proactively unblock work by seeking context or collaboration when needed. Clearly communicate technical decisions, trade-offs, and implementation rationale.
Requirements and Qualifications: Strong experience with Python, including writing production-quality, maintainable code Hands-on experience with PyTorch in real-world ML systems (training and/or inference) Solid understanding of ML fundamentals, including: Model training vs inference Embeddings and representation learning Experimentation and evaluation workflows Experience debugging and maintaining complex, distributed systems Ability to reason through problems, explain solutions, and articulate trade-offs Comfort operating in environments with ambiguity and incomplete requirements.
Preferred Qualifications: Experience building or supporting ML infrastructure platforms Familiarity with feature stores, experimentation frameworks, or inference services Exposure to large-scale, multi-team ML environments Prior work supporting both research and production ML use cases.
Bayside Solutions, Inc. is not able to sponsor any candidates at this time. Additionally, candidates for this position must qualify as a W2 candidate . Bayside Solutions, Inc. may collect your personal information during the position application process. Please reference OpenKyber's CCPA Privacy Policy at
For applications and inquiries, contact: hirings@openkyber.com
Backend Software Engineer: Python-PyTorch W2 Contract Salary Range: $114,400 - $135,200 per year Location: Cupertino, CA - Remote Role
Job Summary: We are seeking experienced AI / ML Infrastructure Engineers to join a central ML/AI platform team responsible for building foundational services used by multiple internal and external product organizations. This role focuses on designing, extending, and supporting scalable ML infrastructure that powers both traditional machine learning and modern LLM-based workflows.
Duties and Responsibilities: Design, develop, and enhance ML infrastructure services supporting training, inference, experimentation, and embeddings lifecycle management. Implement small to medium-sized features across existing ML platform components. Take customer use cases end-to-end, including investigation, debugging, and resolution of issues. Work across the ML stack, collaborating closely with applied scientists and downstream product teams. Diagnose and resolve issues in production ML systems. Navigate ambiguous requirements and proactively unblock work by seeking context or collaboration when needed. Clearly communicate technical decisions, trade-offs, and implementation rationale.
Requirements and Qualifications: Strong experience with Python, including writing production-quality, maintainable code Hands-on experience with PyTorch in real-world ML systems (training and/or inference) Solid understanding of ML fundamentals, including: Model training vs inference Embeddings and representation learning Experimentation and evaluation workflows Experience debugging and maintaining complex, distributed systems Ability to reason through problems, explain solutions, and articulate trade-offs Comfort operating in environments with ambiguity and incomplete requirements.
Preferred Qualifications: Experience building or supporting ML infrastructure platforms Familiarity with feature stores, experimentation frameworks, or inference services Exposure to large-scale, multi-team ML environments Prior work supporting both research and production ML use cases.
Bayside Solutions, Inc. is not able to sponsor any candidates at this time. Additionally, candidates for this position must qualify as a W2 candidate . Bayside Solutions, Inc. may collect your personal information during the position application process. Please reference OpenKyber's CCPA Privacy Policy at
For applications and inquiries, contact: hirings@openkyber.com
