Machine Learning Engineer

Team: IT

Location: US

Commitment: Full-time

Workplace Type: remote

Accountabilities:

• Design and build scalable machine learning services that support intelligent data extraction, classification, enrichment, and augmentation workflows.
• Develop end-to-end ML pipelines covering data preparation, model training, evaluation, deployment, and production monitoring.
• Deploy and optimize machine learning models using technologies such as ONNX, vLLM, TensorRT, and other modern inference frameworks to achieve low latency and high throughput.
• Work closely with software engineers and product teams to define data requirements, feature engineering approaches, model evaluation criteria, and service expectations.
• Build monitoring, observability, and model evaluation systems that maintain high standards for model quality, reliability, and production performance.
• Apply distributed systems and cloud infrastructure principles to support ML services operating at significant scale.
• Continuously research emerging machine learning techniques, model optimization approaches, efficient inference technologies, and large-scale data processing practices.
• Help create reliable, performant ML systems that translate advanced models into measurable value for end users and mission-critical applications.

Requirements:

• 5+ years of professional experience building and deploying machine learning systems in production environments.
• Strong experience with model deployment technologies such as Kubernetes and Ray, as well as inference libraries including ONNX, vLLM, TensorRT, or comparable technologies.
• Proficiency with machine learning frameworks such as PyTorch, TensorFlow, or JAX.
• Demonstrated experience designing and scaling ML services that process large datasets and deliver predictions under demanding latency and throughput requirements.
• Strong understanding of the complete machine learning lifecycle, including data preprocessing, feature engineering, model training, evaluation, deployment, and monitoring.
• Solid software engineering capabilities, including experience with distributed systems, APIs, and cloud infrastructure.
• Strong problem-solving skills and a passion for developing reliable, efficient, and production-ready machine learning systems.
• Ability to collaborate effectively with product and engineering teams and translate technical concepts into practical solutions.
• A proactive, ownership-oriented approach with the ability to work independently and navigate complex technical challenges.
• U.S. Person status is required, as the role involves access to U.S.-only data systems and may be subject to applicable technology export requirements.

Benefits:

• Competitive base salary ranging from $150,000 to $215,000, plus equity.
• Health, dental, and vision insurance.
• Remote-friendly working environment with access to WeWork locations.
• Unlimited paid time off, federal holiday downtime, and company-wide time off at the end of the year.
• 401(k) plan with employer matching.
• Lifestyle and wellbeing stipends.
• Salary top-up during military reserve duty.
• Fully paid parental leave.
• Child and pet care reimbursement during business travel.
• Opportunities for professional growth through training, certifications, and conferences.
• Opportunity to contribute to technically challenging, mission-critical machine learning initiatives.
• Inclusive workplace that welcomes candidates from diverse backgrounds and encourages applicants who may not meet every listed qualification.