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Next Step Systems - National IT Recruiting Firm
Next Step Systems - National IT Recruiting Firm
1 – 10 Darbinieki
B2BPersonāla tehnoloģijas
Next Step Systems is a U.S.-focused IT recruiting firm that connects technology professionals with permanent, full-time roles. Its placements span programming and software engineering, network and cloud engineering, and SAP. Founded in 1995, the firm has expanded its recruiting services through acquisitions, including Parallel Partners, and works with both employers and job seekers.
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Vakances uzņēmumā

Senior Machine Learning Lead Engineer

Lead the systems behind the company’s machine learning, spanning training, evaluation, inference, and deployment. Build production infrastructure with Python, PyTorch or JAX, and GPU computing.

MLMali
160 000 $ – 190 000 $ / gads
AttālinātiPilna slodzeVecākais speciālistsNepieciešamā Valoda: angļuMašīnmācīšanās inženieris
PythonPyTorch

Apraksts

  • Lead the company’s end-to-end machine learning systems, covering data, training, evaluation, inference, and deployment.
  • Develop and improve training and fine-tuning pipelines for large models.
  • Create evaluation systems that measure model capability, robustness, safety, and real-world product performance.
  • Design high-performance inference systems, optimizing latency, GPU utilization, memory, cost, and reliability.
  • Develop data pipelines and systems for high-quality real-world and synthetic training data.
  • Build dependable production infrastructure to deploy, monitor, and continuously improve models.
  • Work with research and application engineering teams to turn model capabilities into product improvements.
  • Make sound technical trade-offs and iterate quickly based on real-world performance.
  • Identify and resolve production issues promptly while limiting user impact.
  • Support and align team members to deliver impactful machine learning work.

Prasības

  • Prior machine learning experience.
  • Experience building and shipping production machine learning systems, beyond research prototypes.
  • Strong knowledge of modern large-model training, fine-tuning, evaluation, and inference.
  • Strong software engineering and systems fundamentals.
  • Experience operating machine learning workloads at meaningful scale, particularly GPU-based systems.
  • Sound technical judgment and ability to work independently on ambiguous problems.
  • A focus on experimentation, measurement, and delivery.
  • High standards for correctness, reliability, and production quality.
  • Experience with Python, PyTorch or JAX, and GPU-based training and inference systems.
  • Willingness to complete a 60-minute coding assessment.

Priekšrocības

  • Medical insurance
  • Dental coverage
  • Vision coverage
  • Savings plan options
  • Paid time off

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