ML Platform Engineer & Research Innovator

Career Techniques; New York (NY); Hybrid; USD 200,000 - 300,000; Full time

Job summary

Career Techniques in New York is seeking an experienced ML researcher to expand our distributed ML stack, benchmark workloads, and stress-test both software and hardware across the platform. You will build high-level abstractions, integrate tooling with data frameworks, and enable rapid experimentation using Ray.

The role requires hands-on ML experience with PyTorch/TensorFlow, scalable ML deployment, and familiarity with AI agent workflows.

Qualifications

• Strong software engineering foundation in Python and API design.
• Hands-on experience with modern frameworks (PyTorch, TensorFlow) and large-scale deployment.
• Experience scaling ML workloads across GPUs and multi-node clusters.
• Familiarity with AI agent workflows and LLM tooling.
• Ability to identify bottlenecks across hardware and software (memory, GPU utilization, data pipelines).

Responsibilities

• Platform Validation & Infrastructure Benchmarking: test training and inference environments.
• Streamline Rapid Prototyping for ML Research: build abstractions and integrate core ML tooling.
• Agentic Workflows for ML Research: leverage AI agents to generate experiments and stress-test clusters.
• Research Platform Feedback & Insights Sharing: publish empirical findings and advise engineering teams.

Skills

Python

APIs

PyTorch

TensorFlow

Distributed Compute

Ray

Dask

Tools

Ray

Dask

PyTorch Distributed

Job description

Career Techniques in New York is seeking an experienced ML researcher to expand our distributed ML stack, benchmark workloads, and stress-test both software and hardware across the platform. You will build high-level abstractions, integrate tooling with data frameworks, and enable rapid experimentation using Ray.

The role requires hands-on ML experience with PyTorch/TensorFlow, scalable ML deployment, and familiarity with AI agent workflows.