Research Engineer - Machine Learning
Job in
New York, New York County, New York, 10261, USA
Listing for:
True3D
Full Time
position
Listed on 2026-01-14
Job specializations:
-
Engineering
Systems Engineer, Software Engineer
-
IT/Tech
Systems Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly
USD
125000.00
150000.00
YEAR
Job Description & How to Apply Below
Location: New YorkResearch Engineer - Machine Learning and Systems
Location: New York City Office HQ
Employment Type: Full time
Department: Research
Overview
We are hiring a principal level Research Engineer with deep strength in machine learning or 3D graphics, software engineering, and systems design. You will bridge frontier research with production systems and ship advanced models used in real products. The work spans exploration, rapid prototyping, rigorous experimentation, and dependable production deployment. Expect to push the limits of spatial intelligence and controllable graphics while keeping systems robust, scalable, and cost efficient.
Role
You will partner with research, engineering, and product to design, build, and operate large models and high performance systems. You will set technical standards, mentor others, and raise the bar for research quality, code quality, and reproducibility.
Key responsibilities
Research, design, and implement models and systems across vision, generative modeling, simulation, rendering, and 3D perceptionBuild data, training, evaluation, and deployment pipelines with strong observability and reproducibilityTranslate research insights into reliable production services that meet product and latency requirementsContribute hands on across prototyping, optimization, integration, and scalingSurvey new methods and run grounded evaluations to identify what to adopt and whenShare expertise through design reviews, mentoring, and documentationMinimum qualifications
PhD in Computer Science, Machine Learning, Computer Graphics, Computer Vision, or related field, or equivalent research track recordSeven or more years of experience in applied ML or research engineering including significant time in fast paced or startup settingsStrong publication record in top venues such as NeurIPS, ICLR, ICML, CVPR, ECCV, ICCV, SIGGRAPH, or TOG with multiple first author papers or equivalent impactful artifactsProven experience training and serving large models at scale including multi GPU or multi node training, distributed data loading, mixed precision, and memory optimizationFluency in Python and C++ and experience writing efficient CUDA or Triton kernelsExpertise with PyTorch or JAX and modern tooling for experiment tracking, evaluation, and deploymentDemonstrated ability to take ideas from paper to production with measurable impact on users or business outcomesStrong systems skills including profiling, performance tuning, reliability engineering, and cost awarenessExcellent communication with the ability to work across research and product teamsPreferred qualifications
Contributions that are widely used in the community such as open source libraries, datasets, or benchmarks with visible adoptionExperience in neural rendering, differentiable rendering, 3D reconstruction, volumetric video, SLAM, geometric deep learning, or simulationExperience operating large training jobs on Kubernetes, Slurm, or Ray across public cloud environmentsExperience with evaluation and safety for generative or interactive models including red teaming and guardrail designTrack record of mentoring teams and setting research and engineering best practicesPatents or awards that recognize technical contributionsNice to have
Shipped interactive graphics or 3D systems with strict real time constraintsExperience building custom compilers or graph level optimizations such as CUDA graphs, XLA, or graph capturePrior leadership in cross functional initiatives spanning data, infra, and productHow to applyPlease include a CV, links to publications, code, and a brief summary of two projects that best represent your impact. Include details on model scale, data scale, latency or throughput targets, and the concrete results you achieved.
On site in New York City required. Relocation support available.
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