Senior Machine Learning Engineer (AI)

TL;DR

Senior Machine Learning Engineer (AI): Building and deploying machine learning models and production analytics across image, video, text, geospatial, time series, and structured data with an accent on operationalizing models into reliable, scalable AI capabilities. Focus on designing and implementing core product functionality, orchestrating automated data/analytics pipelines, and enabling mission-critical field work while meeting US security clearance requirements.

Location: Austin, Texas or Remote

Salary: $160,000–$200,000/year

Company

hirify.global builds AI systems that connect data, models, and business outcomes for reliable deployment and ongoing optimization.

What you will do

• Work with customers and stakeholders to define requirements and deliver solutions using the Chariot AIOps platform.
• Develop machine learning models and custom analytics for unstructured and structured data (image, video, text, geospatial, time series, structured).
• Orchestrate and automate complex data engineering and analytics pipelines.
• Envision, specify, and implement core product functionality for hirify.global software products.
• Collaborate with data scientists, software engineers, and DevOps engineers to transform ML models into operational capabilities.
• Participate in mission-critical field work and support deployments in unpredictable environments.

Requirements

• US citizenship and eligibility to obtain and maintain a Secret (or above) US security clearance.
• BS in computer science, machine learning, or related field plus 6+ years of relevant experience.
• Proven experience delivering data-centric systems (data engineering, data cleaning, ETL pipelines, ML, production analytics).
• Strong Python expertise; knowledge of TensorFlow, PyTorch, and/or scikit-learn.
• Solid software engineering fundamentals (algorithms, data structures, design patterns) and at least one systems programming language (e.g., Go, Rust, C++, Java, Scala).
• Experience with modern engineering tools and processes (Agile, version control, issue tracking, CI/CD, debugging).

Nice to have

• Advanced degree in data science, machine learning, computer science, or related discipline.
• Experience with client-server architectures and design patterns (async programming, REST, GraphQL, React, Vue, Angular).
• Experience deploying software in containerized/cloud environments (Docker, Kubernetes, infrastructure as code, major cloud architectures).
• Experience building agentic systems, agentic workflows, or AI agents.
• Experience leading a small team and delivering solutions in secure government environments.

Culture & Benefits

• Fully remote work environment, or hybrid/on-site work at the office in northwest Austin, TX.
• Up to 25% travel time.
• Medical/dental/vision insurance, voluntary life and disability coverage, and HSA/FSA plans (including dependent care FSA).
• 401(k) plan, unlimited PTO, and paid parental leave.
• Competitive total compensation including base salary, equity grants, and cash bonuses.

Hiring process

• Interviews to assess ML engineering experience, production/data pipeline work, and ability to operate in secure government environments.
• Technical evaluation focused on building and operationalizing ML systems.
• Final discussions to confirm fit and clearance-related requirements.