Job Title: Software Engineer I
Duration: 12 months (Possibility to extend based on experience and business needs)
Location: Remote
Summary:
- Client is seeking a strong System / Machine Learning Engineer to join our Fundamental AI Research (FAIR) team, an organization focused on making research breakthroughs in AI.
- Responsibilities include working with deep learning codebases that support training cutting-edge AI/ML models creating high quality results, and bringing the latest research advancements to client products for connecting billions of users.
- The chosen candidate will work with a diverse and highly interdisciplinary team of scientists, engineers, and cross-functional partners, and will have access to cutting edge technology, resources, and research facilities.
Must-Have Skills:
- 0-1 years of deep learning experience working with codebases supporting cutting-edge AI/ML models.
- Proficiency in ML Development: Experience developing machine learning algorithms or infrastructure in Python/PyTorch and/or C/C++.
- Core Education: Degree in Computer Science, Computer Engineering, or a relevant technical field.
Nice-to-have Skills:
- Demonstrated Software Engineering Track Record: Proven experience via professional work, coding competitions, or widely used open source/GitHub contributions.
Years of Experience:
- 0-1 years of deep learning experience working with codebases supporting Cutting edge AI/ML models.
Degrees/Certifications Required:
- Bachelor Degree in Computer Science, Computer Engineering or relevant Technical field.
- PHD or advanced degree preferred
Key Projects / Day-to-Day Responsibilities:
- Engineer, design, implement, and improve cutting-edge machine learning systems and tools for enabling research
- Apply knowledge of relevant research domains, along with expert coding skills, to platform and framework development projects
- Write clean and robust machine learning code
Purpose/Size of this team & where does this position fit within the team:
- The position sits within the Fundamental AI Research (FAIR) team, a highly interdisciplinary organization focused on making research breakthroughs in AI and bringing the latest research advancements to client products. This role falls within the research engineering space - working directly with different research teams to enable them to connect their research, training ML models, collecting data, writing evaluations, publishing/making code base available to others, being able to share this research. Writing code across the entire life cycle, not just training ML models. Troubleshooting.
How will performance be measured:
- Performance will be measured by the ability to engineer, design, implement, and improve cutting-edge ML systems and tools, as well as writing clean, robust machine learning code that enables research and product deployment.
What makes this role attractive to top talent, and what unique value does it offer to the ideal candidate:
- Opportunity to work alongside world-class scientists and engineers on state-of-the-art AI/ML models, backed by access to cutting-edge technology, compute resources, and research facilities impacting billions of users.
Interview Process:
- How many rounds of interviews? 1 (2 likely)
- Types of Interviews 1 hour interview, technical/behavioral
- Interview Duration 1 hr
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Spectraforce Technologies
Sep 18, 2026