This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Machine Learning Engineer based in United States.
This role offers the opportunity to build production-grade machine learning systems that support mission-critical data enrichment and decision-making.
You will work across the full ML lifecycle, from model development and training through deployment, optimization, and monitoring.
As a technical leader, you will design scalable services capable of processing large volumes of data while meeting demanding performance standards.
You will collaborate closely with software engineers and product teams to translate complex requirements into reliable ML solutions.
The role combines advanced machine learning with distributed systems, cloud infrastructure, and high-performance inference technologies.
You will help establish robust engineering practices around observability, evaluation, and production reliability.
This is an impactful opportunity for an experienced ML engineer who enjoys solving challenging technical problems in a fast-moving environment.
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.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
#LI-CL1
