
Machine Learning Engineer (Remote)
Hired · United States
- Hybrid
- Part-time
- $120,000 / year
- United States
Job highlights
- Work on real-world ML systems evaluations.
- Build and modify ML training pipelines.
- Develop production-grade ML codebases.
- Collaborate on AI system design and deployment.
- Utilize TensorFlow, PyTorch, Python, and cloud.
About the role
Machine Learning Engineer (Remote)
We are hiring for one of our clients, seeking MLE Bench – ML Engineers to work on a part-time basis. As an MLE Bench – ML Engineers, you will contribute to benchmark-driven evaluation projects focused on real-world machine learning systems. You will work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems. This role is critical in the AI industry, where our client's cutting-edge research and expertise are applied to help enterprises transform AI from proof of concept into proprietary intelligence.
Key Responsibilities:
- Work with real-world ML codebases to support MLE bench-style evaluation tasks, building, running, and modifying model training, evaluation, and infrastructure workflows.
- Collaborate with cross-functional teams to design, implement, and deploy AI systems that meet the highest standards of performance, reliability, and scalability.
- Develop and maintain production-grade ML codebases, ensuring high-quality, efficient, and maintainable code that meets the client's requirements.
- Participate in the development of model training and evaluation pipelines, ensuring accurate and reliable results that meet the client's expectations.
- Work with data scientists and engineers to design and deploy AI systems that integrate with real-world data sources and provide actionable insights.
Required Skills & Qualifications:
- 3+ years of experience in machine learning engineering, with a strong focus on research and development of AI systems.
- Expertise in machine learning frameworks (e.g., TensorFlow, PyTorch) and programming languages (e.g., Python, R).
- Strong understanding of software development principles, including testing, version control, and continuous integration.
- Experience with cloud-based infrastructure (e.g., AWS, GCP, Azure) and containerization (e.g., Docker).
- Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams.
More About the Opportunity:
This role offers a unique opportunity to work with a global leader in the AI industry, where you will contribute to cutting-edge research and development of AI systems that transform the way enterprises operate. As an MLE Bench – ML Engineers, you will have the opportunity to work on a variety of projects, collaborating with experts in the field and developing your skills in machine learning engineering.
Equal Opportunity Employer:
We hire based on skills and expertise. All qualified candidates are welcome regardless of background, experience, or prior employment history. Applications are reviewed solely on demonstrated technical ability and qualifications.
Apply Now!
Key skills/competency:
- Machine Learning Engineering
- AI Systems Development
- Model Training & Evaluation
- Production-grade ML Codebases
- Cloud Infrastructure (AWS, GCP, Azure)
- Containerization (Docker)
- TensorFlow
- PyTorch
- Python
- Software Development Principles
Skills & topics
- Machine Learning Engineer
- Machine Learning
- AI
- Deep Learning
- Python
- TensorFlow
- PyTorch
- AWS
- GCP
- Azure
- Docker
- Software Engineering
- Data Science
- Remote Work
- Part-time
How to get hired
- Tailor your resume: Highlight your 3+ years of ML engineering experience and proficiency in Python, TensorFlow, or PyTorch.
- Showcase cloud & container skills: Emphasize experience with AWS, GCP, Azure, and Docker.
- Demonstrate collaboration: Provide examples of working with cross-functional teams on AI systems.
- Prepare for technical interviews: Be ready to discuss software development principles and ML evaluation tasks.
Technical preparation
Behavioral questions
Frequently asked questions
- What is the work arrangement for the Machine Learning Engineer role at Hired?
- The Machine Learning Engineer role at Hired is fully remote, allowing you to work from anywhere. This offers flexibility and the opportunity to collaborate with a global team.
- What specific ML frameworks are essential for this Machine Learning Engineer position?
- Expertise in machine learning frameworks such as TensorFlow and PyTorch is essential for this Machine Learning Engineer role. Proficiency in Python is also a key requirement.
- How does Hired ensure fair hiring for Machine Learning Engineer applicants?
- Hired prioritizes skills and expertise. All applications for the Machine Learning Engineer role are reviewed based on demonstrated technical ability and qualifications, ensuring equal opportunity.
- What kind of projects can I expect as a Machine Learning Engineer at Hired?
- As a Machine Learning Engineer, you will work on benchmark-driven evaluation projects for real-world AI systems, focusing on model training, evaluation, and deployment workflows.
- Is this Machine Learning Engineer role full-time or part-time?
- This Machine Learning Engineer role is part-time, focusing on MLE bench-style evaluation tasks.