Senior ML Ops Engineer

Responsibilities

• Design and implement end-to-end scalable machine learning systems.
• Own the full MLOps lifecycle, including evaluation techniques, statistical modeling, and metric generation.
• Manage model deployment, monitoring, and prompt engineering.
• Perform ML model optimization using techniques such as quantization, pruning, or speculative decoding.
• Identify and resolve system-level bottlenecks to optimize ML model performance.
• Collaborate with cross-functional teams and provide clear technical documentation.

Requirements

• Proven experience designing and implementing scalable ML systems within the last 12 months.
• Proficiency in Python and Java (including library/dependency and package management).
• Hands-on experience with machine learning frameworks such as TensorFlow or PyTorch.
• Strong understanding of DevOps principles and tools, including CI/CD pipelines and Terraform.
• Expertise in containerization technologies like Docker and Kubernetes.
• Excellent communication skills with the ability to lead inter-team discussions and abstract complex technical details.

Preferred Qualifications

• Experience with the GCP ML tech stack.
• Proficiency with Infrastructure as Code (IaC).
• Experience with big data technologies such as Apache Spark or Hadoop.
• Knowledge of on-device ML system development.
• Experience with data analytics to identify anomalies, skew, and discrepancies.
• Understanding of the ethical implications of machine learning, such as selection bias.

Benefits

• Competitive compensation based on experience.
• Medical, vision, and dental benefits.
• 401k retirement plan.
• Variable pay and incentives.
• Paid time off and holidays.

About the Company

Photon has spent the last 20 years powering digital experiences for Fortune 500 companies. With over 4,000 team members globally, we are dedicated to driving digital modernization and delivering high-impact solutions for our clients.