Staff Machine Learning Engineer (AI)

TL;DR

Staff Machine Learning Engineer (AI): Building and optimizing AI-first SaaS products that leverage Large Quantitative Models (LQMs) and emerging agentic frameworks with an accent on the end-to-end ML lifecycle, data pipelines, and scalable production deployment. Focus on rapidly iterating on solutions, evaluating new models, and bridging cutting-edge AI concepts with functional, real-world MVPs.

Location: Remote (United States). Pay is tiered based on location: Tier 1 for candidates located within 75 miles of San Francisco, Los Angeles, Seattle, New York, Boston, and Washington, DC; Tier 2 for all other US locations.

Compensation: $173,922–$286,000

Company

hirify.global is a high-growth company delivering AI solutions that address some of the world's greatest challenges, having emerged as an independent company from Alphabet Inc. in 2022.

What you will do

• Design, construct, and manage robust data pipelines for the training, validation, and continuous retraining of Large Quantitative Models (LQMs) and agentic frameworks.
• Develop, implement, and rigorously test novel ML models and algorithms, defining appropriate metrics to ensure model performance aligns with high-level product objectives.
• Lead the effort in cleaning, transforming, and engineering features from complex and large-scale datasets to optimize LQM performance and predictive accuracy.
• Conduct deep analysis of model behavior, performance, and failure modes, tuning hyper-parameters and optimizing model architecture for efficiency, speed, and accuracy in a production context.
• Collaborate closely with AI researchers, product managers, and software engineers to translate high-level business objectives into actionable ML development and deployment roadmaps.
• Drive technical execution with high autonomy, making critical design and implementation decisions independently and championing exceptional engineering standards for code quality, system efficiency, and security.

Requirements

• BS in Software Engineering, Computer Science, or equivalent field of study.
• 8+ years of postgraduate experience in software development.
• Experience developing highly-available, performant, scalable ML systems, including large-scale data processing pipelines.
• Strong expertise in Python, including the ML stack (PyTorch, TensorFlow, JAX, NumPy, Pandas).
• Long, successful history of driving the full ML lifecycle: from initial data exploration and hypothesis testing to architecture, model training, evaluation, and production deployment.
• Deep proficiency in MLOps and software best practices, including CI/CD for ML, experiment tracking (e.g., Weights & Biases, MLflow), automated testing, and version control for both code and datasets.

Nice to have

• MS or PhD in Software Engineering, Computer Science or equivalent experience.
• Financial simulation or technical experience, risk simulation.
• Experience with scalable software development on cloud computing platforms (e.g., GCP, AWS).

Culture & Benefits

• Competitive base salary, performance-based incentives or bonuses, and equity participation.
• Comprehensive medical, dental, and vision coverage for employees and dependents, with generous employer premium contributions.
• Retirement savings with company matching, paid parental leave, and inclusive family-building benefits.
• Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance.
• Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs.