Machine Learning Engineer
WFA Digital Insight
The demand for skilled machine learning engineers has skyrocketed, with a 25% increase in remote job postings in the past year. As companies like mercor invest heavily in AI research, the need for experts who can bridge the gap between technical and creative teams has never been more pressing. With the global AI market projected to reach
Job Description
About the Role
Machine learning engineers play a crucial role in driving innovation and growth in the tech industry. At mercor, you will have the opportunity to work with elite creative and technical talent, guiding research and engineering teams to close knowledge gaps in AI and data science. As a machine learning engineer, you will be responsible for designing challenging agentic tasks, developing evaluation frameworks, and collaborating with subject matter experts to ensure consistency and accuracy in training data.The role requires a strong foundation in machine learning, data science, and software engineering, as well as excellent written communication skills. You will be working closely with cross-functional teams, including research and engineering teams, to identify areas of improvement and develop solutions that drive results. If you are passionate about AI and machine learning, and have a strong desire to work on complex problems, this role is an excellent opportunity to take your career to the next level.
Mercor is committed to fostering a culture of innovation and collaboration, and is headquartered in San Francisco. With a strong team of investors, including Benchmark, General Catalyst, and Peter Thiel, mercor is well-positioned to make a significant impact in the AI research market.
What You Will Do
- Guide research and engineering teams to close knowledge gaps in AI and data science domains
- Surface nuances that distinguish expert-level work from surface-level reasoning
- Design challenging agentic tasks rooted in real-world ML, data science, data engineering, and software workflows
- Write accurate, well-documented solutions that serve as ground truth
- Evaluate AI agent outputs against your solutions
- Provide detailed written feedback capturing correctness, efficiency, and reasoning quality
- Develop and refine evaluation frameworks and rubrics for assessing agentic behavior on AI and data science tasks
- Collaborate with other subject matter experts to ensure consistency and accuracy in training data
- Participate in the development of new AI and machine learning models
- Stay up-to-date with the latest advancements in AI and machine learning
What We Are Looking For
- 3+ years of research, academic, or industry experience in machine learning, data science, software engineering, computer science, statistics, biology, electrical/mechanical/civil engineering, physics, chemistry, mathematics, materials science, or other STEM background
- Demonstrated technical expertise in programming, data analysis, ML modeling, statistical methods, or computational methods
- Ability to commit to 40 hours per week during weekdays for the duration of the engagement
- Strong written communication skills and the ability to explain technical decisions clearly
- Experience with data annotation, labeling, evaluation, or human feedback collection
- Experience with LLMs, AI systems, or agentic workflows
- Familiarity with agentic frameworks
Nice to Have
- Prior experience with data annotation, labeling, evaluation, or human feedback collection
- Experience with LLMs, AI systems, or agentic workflows
- Familiarity with agentic frameworks
- Experience with cloud-based technologies such as AWS or Azure
- Experience with containerization using Docker
Benefits and Perks
- Competitive hourly rate ($70-00/hour)
- Opportunity to work with a leading AI research company
- Collaborative and dynamic work environment
- Flexible remote work arrangement
- Access to cutting-edge technologies and tools
- Professional development opportunities
- Recognition and reward for outstanding performance
- Comprehensive benefits package, including health, dental, and vision insurance
- Generous PTO policy
- Remote work stipend
- Access to a network of talented professionals in the AI and machine learning community
How to Stand Out
- Make sure to highlight your technical expertise in machine learning, data science, and software engineering in your resume and cover letter.
- Be prepared to provide examples of your experience with data annotation, labeling, evaluation, or human feedback collection.
- Showcase your ability to explain complex technical concepts in a clear and concise manner.
- Demonstrate your knowledge of agentic frameworks and experience with LLMs, AI systems, or agentic workflows.
- Be prepared to discuss your experience with cloud-based technologies and containerization using Docker.
- Tailor your application materials to the specific requirements of the role, and be sure to follow the application instructions carefully.
- Consider creating a portfolio that highlights your machine learning and data science projects, and be prepared to discuss your work in detail during the interview process.
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