Senior Machine Learning Engineer

Phiture; United States; Remote; USD 120,000 - 160,000; Full time

Job summary

A leading technology consulting firm seeks a Senior Machine Learning Engineer to develop advanced ML frameworks for large-scale applications. You will work at the forefront of AI enablement, enhancing ML workflows and collaborating with cross-functional teams on innovative projects. The role offers opportunities for professional development and to work on bleeding-edge technologies.

Benefits

Opportunity to work on bleeding-edge projects

Flexible schedule

Professional development opportunities

Work with a highly motivated team

Competitive salary

Qualifications

• 5+ years proficiency in Python and ML packages like PyTorch, TensorFlow, or JAX.
• Strong understanding of ML principles, particularly with LLMs.
• Experience building scalable deep learning systems and large-scale data infrastructure.

Responsibilities

• Build ML tooling for the full lifecycle from model training to deployment.
• Collaborate with stakeholders for aligning LLMs with specific use cases.
• Deliver reusable tooling integrated with existing ML systems.

Skills

Python

Machine Learning Principles

Communication Skills

Education

BS/BA in Computer Science or equivalent

Tools

PyTorch

TensorFlow

JAX

Java

Scala

Job description

Join a highly skilled engineering team building advanced machine learning frameworks to support large-scale model training, fine-tuning, and evaluation. This project plays a foundational role in accelerating ML development workflows and enhancing model performance through continuous infrastructure innovation and tooling development. You’ll work at the core of AI enablement—developing systems and frameworks that power large language models (LLMs) and cutting-edge deep learning applications.

As a Senior Machine Learning Engineer, you will design and implement scalable, reusable tooling that supports the full ML lifecycle—from data processing and model training to evaluation and deployment. You'll collaborate across engineering, research, and product teams to align LLMs with domain-specific requirements and deliver high-impact machine learning infrastructure.

Responsibilities

• Build machine learning tooling to facilitate various phases of the ML lifecycle from model training, data ETL, end-to-end model evaluation and deployment
• Work with technical and non-technical stakeholders to build solutions to align LLMs for specific use cases
• Deliver reusable and easy-to-use tooling to integrate with existing data and machine learning systems
  
  

Requirements

• 5+ years of proficiency in Python, including machine learning packages like PyTorch, TensorFlow, or JAX
• Strong understanding of machine learning principles, especially in the context of LLMs
• Skills in Java/Scala (preferred)
• Experience building scalable deep learning systems
• Experience with large scale data infrastructure
• Strong verbal and written communications skills with the ability to work effectively across internal and external organizations and virtual teams
• BS/BA or equivalent degree in computer science or similar (preferred)
  
  

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Professional development opportunities
  
  

About Us

Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.