Machine Learning Engineer (AI)

Location: San Francisco, United States; on-site

Base salary: $120,000–$180,000 per year; stock options may be offered separately.

Company

hirify.global operates Deploy, an AI infrastructure platform providing access to open-source and proprietary models, including optimized inference and models for content safety, deepfake detection, sponsorship intelligence, and IP and publicity protection.

What you will do

• Design and code neural networks, gather and refine data, train and tune models, and deploy them to production at scale with high throughput and uptime.
• Analyze production results and continuously improve model accuracy and speed.
• Prototype state-of-the-art deep learning models and build scalable, maintainable data pipelines for terabyte-scale and million-file datasets.
• Collaborate closely with Backend, DevOps, and internal data-labeling services.
• Apply OWASP Top 10 techniques, maintain data-handling best practices, protect information assets, and report security or policy violations.

Requirements

• Undergraduate or graduate degree in computer science or a similar technical field, with significant coursework in mathematics or statistics.
• 1–2 years of industry machine learning experience.
• Experience training and deploying a deep learning model for image, NLP, video, or audio into production, with measurable performance improvement over a baseline; industry or personal-project experience is accepted.
• Strong experience with a high-level machine learning framework such as TensorFlow, Caffe, or Torch, plus familiarity with the other frameworks.
• Strong Python skills, especially for machine learning frameworks.
• Ability to quickly code and prototype data pipelines using combinations of Python, Node, Bash, and Linux command-line tools for large datasets containing millions of files.
• Working knowledge of C++, Scala/Spark, SQL, Cassandra, and Docker.
• Current knowledge of deep neural network research and architectures, including their theory, motivations, and implementation in a machine learning framework.
• Strong communication and collaboration skills, a team-player mindset, and willingness to take ownership and do whatever is required.

Culture & Benefits

• Work on AI model inference and proprietary AI products used by large organizations.
• Opportunity to contribute directly to a fast-growing AI startup.
• Steep learning curve and exposure to technologies across the machine learning stack.
• On-site work in San Francisco.
• Stock options may be offered in addition to base salary.

Hiring process

• AI tools may support application review, resume analysis, response assessment, and verification-signal identification.
• Human reviewers make the final hiring decisions.