New

Software Engineer III - Senior Research Engineer

Spectraforce Technologies
United States, North Carolina, Raleigh
500 West Peace Street (Show on map)
Apr 29, 2026
Job Title: Software Engineer III - Senior Research Engineer Location: Remote Duration: 1 year, possibility for extension. Job Description Senior Research Engineer Client is seeking a strong Senior Machine Learning Engineer to join our 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 Meta 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 HARD Skills 5-10 years of Python experience 3-5 years of Pytorch experience 5+ years of Distributed ML Training (FSDP/DDP) experience 3-5 years of Dataset / Pytorch DataLoader experience Nice-to-have Skills Demonstrated software engineering experience via work experience, or widely used contributions in open source repositories (e.g. GitHub) Prior contributions to open-source AI/ML projects 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 Contribute to open-source projects 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++ Experience with machine learning frameworks such as PyTorch and distributed optimization techniques such as FSDP/DDP Experience working with large datasets and data pipelines Solid understanding of algorithms, data structures, and software engineering best practices. Demonstrated ability to work collaboratively in a fast-paced, team-oriented environment. Excellent problem-solving and communication skills. Preferred Qualifications Demonstrated software engineering experience via work experience, or widely used contributions in open source repositories (e.g. GitHub) Prior contributions to open-source AI/ML projects Story Behind the Need - Business Group & Key Projects Key Projects/Day-to-Day Responsibilities: 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 Meta 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 Purpose/Size of this team & where does this position fit within the team? Team size 3. Additional Engineering resources to meet demand. How will performance be measured? Completion and quality of engineering tasks. Compelling Story & Candidate Value Proposition What makes this role interesting? This is working on cutting-edge Machine Learning training and inference code to create State of the Art research models. It's working with leading researchers in the field. Value added or experience gained Cutting edge distributed training for creating state of the art ML models. Are there any types of candidate profiles or skills that may not be the right fit for this team? Pure software engineers will not be a good fit. Experience with Large scale Model training with Pytorch is essential. What are some difficulties that the candidate should be aware they may face in the role and need to be able to handle to be successful? Strong technical and communication skills will be needed to succeed in a fast-paced and ambiguous environment. Interview Process: How many rounds of interviews? Who will be conducting each round? 1-2. We'll setup a pool of interviewers to process the queue quickly. Types of Interviews (behavioral, technical, presentation, etc.) What should the contractor expect to talk about or what should they 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. Interview Duration 1 hr