Job Title: Systems / ML Engineer III
Duration: 12 Months (possibility for extension)
Location: Remote (Ideally EST, but anywhere in NORAM should work)
Job Description:

• Client is seeking a strong System / Machine Learning Engineer to join their Fundamental AI Research (FAIR) team, an organization focused on making research breakthroughs in AI
• Responsibilities include developing deep learning libraries that support large-scale distributed training, open sourcing high quality code and reproducible results for the community and bringing the latest research 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.

Top 3 Skill Sets:

• Pytorch
• Machine Learning
• Python

Nice-to-have Skills:

• Distributed training for ML models
• Building Open-Source Libraries for Machine Learning
• Experience with Machine Learning Research, publishing papers

Years of Experience:    

• 5-10

Degrees/Certifications Required:

• Computer Science / Engineering

Responsibilities:

• Engineer, design, implement, and improve highly scalable 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.

Minimum Qualifications:

• Degree in Computer Science, Computer Engineering or relevant technical field
• 5+ years’ experience with deep learning.
• Experience developing machine learning algorithms or machine learning infrastructure in Python or C/C++

Preferred Qualifications:

• Demonstrated software engineering experience via work experience, coding competitions, or widely used contributions in open-source repositories (e.g. GitHub)
• Experience in open-source development.

How many rounds of interviews?         

• 1-2. We’ll setup a pool of interviewers to process the queue quickly.
• Types of Interviews (behavioral, technical, presentation, etc.)

What should the candidate expect to talk about or what should you prepare:

• Mostly technical:  experience with distributed training. How DDP/FSDP works, what are different parallelism techniques to scale models, what are their tradeoffs, which one would you use in which case, some back of the envelope calculation of memory/throughput requirements, so on.

 
 
At SPECTRAFORCE, we are committed to maintaining a workplace that ensures fair compensation and wage transparency in adherence with all applicable state and local laws. This position’s starting pay is: $ 85.00/hr.