Senior Machine Learning Engineer

Eviden; United States; Remote; USD 135,000 - 307,000; Full time

Job summary

An established industry player seeks a skilled MLOps Engineer to enhance machine learning operations. This role involves integrating recommender systems into products, managing feature stores, and ensuring high-quality data for ML models. The ideal candidate will collaborate with cross-functional teams to optimize ML systems and drive data-driven decisions. Join a dynamic team where your contributions will significantly impact innovative projects in the tech landscape. If you have a passion for machine learning and a desire to work in a fast-paced environment, this opportunity is perfect for you.

Qualifications

• Experience in software engineering and integrating ML systems.
• Strong knowledge of feature store management and data integrity.

Responsibilities

• Monitor and optimize ML systems in production.
• Collaborate with data engineers and scientists for data management.

Skills

Software Engineering

AB Testing

Data Management

Machine Learning Operations

Feature Store Management

Data Integration

Monitoring ML Systems

Education

Bachelor's Degree in Computer Science or related field

Tools

Vertex AI Feature Store

BigTable

BigQuery

Job description

Direct message the job poster from Eviden

Human Resource Specialist at Atos - (Atos is a global leader in digital transformation with 105,000 employees in 73 countries).

Job title: MLOPS Engineer

Locations: REMOTE

Type: Full-time with Eviden (An ATOS Business)

Job Description:

1. Apply software engineering skills to collaborate with teams integrating recommender systems into customer-facing products.
2. Utilize experience in A/B testing and iterative optimization based on data-driven approaches.
3. Understand infrastructure needs for deploying ML systems, including CPU/GPU and networking infrastructure. Manage features efficiently at scale using Vertex AI Feature Store, ensuring transparency and security in ML operations.
4. Assist with data labeling and management to ensure high-quality data for ML models. Collaborate with data engineers and scientists to maintain data integrity and efficiency, integrating data sources like BigTable and BigQuery for business intelligence.
5. Monitor ML systems in production, identify opportunities for improvement, and implement optimizations. Participate in support rotations and calls as needed.

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Information Technology

Industries

• IT Services and IT Consulting, Retail

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