11 days ago
Base Salary
$120k - $180k/yr
Responsibilities
- Design, code, train, tune, deploy, and improve neural network models for production use cases.
- Gather and refine data, analyze model performance in production, and continuously improve accuracy and speed.
- Deploy machine learning models at scale with high throughput and uptime.
- Build scalable and maintainable data pipelines for large datasets.
- Collaborate closely with Backend, DevOps, and internal data-labeling teams.
- Apply OWASP Top 10 techniques and follow information-security policies and procedures.
- Report suspected security or policy violations and breaches.
Requirements
- Undergraduate or graduate degree in computer science or a similar technical field, with significant mathematics or statistics coursework.
- 1–2 years of industry machine learning experience.
- Experience training and deploying a deep learning model for image, NLP, video, or audio with measurable improvement over a baseline, either professionally or as a personal project.
- Strong experience with a high-level machine learning framework such as TensorFlow, Caffe, or Torch, with familiarity with the others.
- Strong Python skills, particularly for machine learning frameworks.
- Ability to prototype data pipelines using Python, Node, Bash, and Linux command-line tools for large datasets.
- Working knowledge of C++, Scala/Spark, SQL, Cassandra, and Docker.
- Current understanding of deep neural network research, architectures, theory, motivations, and implementation.
- Strong communication, collaboration, and teamwork skills.
Benefits
- Company-sponsored health, vision, and dental insurance.
- Gym membership.
- Paid vacation according to company policy.
- Potential equity grant in the form of a stock option.
- Expected base salary range of $120,000–$180,000.
- The company operates across offices in San Francisco, Seattle, New York, and Delhi; no specific work arrangement is stated.