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TinyFish

Senior ML Engineer

Reposted Yesterday
Remote or Hybrid
Hiring Remotely in United States
160K-240K Annually
Senior level
Remote or Hybrid
Hiring Remotely in United States
160K-240K Annually
Senior level
Design, train, and deploy scalable ML models (generative, classification, regression). Define feature roadmaps, collaborate with engineering to implement code and APIs, adapt ML methods for distributed/GPU environments, and create evaluation/annotation programs for fine-tuning and performance measurement.
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Senior ML EngineerResponsibilities
  • Develop highly scalable ML products by training and deploying generative, classification, and regression models key to TinyFish's underlying products.

  • Suggest, collect and synthesize requirements and create effective feature roadmap.

  • Code deliverables in tandem with the engineering team.

  • Adapt standard machine learning methods to best exploit modern parallel environments (eg distributed clusters, multicore SMP, and GPU).

  • Work on a range of classification and optimization problems that might include web agent automation, entity resolution, search, ranking and retrieval, and others as needed.

  • Design evaluation and annotation programs to enable model and web agent reinforcement training, fine tuning, and performance evaluation.

Qualifications
  • BS or MS in Computer Science, Electrical Engineering, Machine Learning, or a related field

  • 3+ years of hands-on experience designing and training ML models to solve real world problems.

  • Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow

  • Strong software engineering skills: data structures, algorithms, distributed systems design, and API development

  • Familiarity with scalable data processing frameworks such as Apache Spark, Beam, or other systems.

  • Track record of consistently improving model or overall system performance to achieve business outcomes.

  • Excellent problem-solving aptitude and the ability to work cross-functionally in a fast-paced startup environment

  • Clear communicator who can distill complex AI concepts for technical and non-technical stakeholders

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