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Senior Machine Learning Ops Engineer Jobs in Pennsylvania

Elsevier

Senior ML Ops Engineer

Philadelphia, PA · On-site

$99K - $137K/yr

In this role, the Senior Machine Learning Engineer will bridge Data Science and Engineering to develop AI-based features and ensure the deployment of secure, reliable, and scalable machine learning ...

TeleTracking

Machine Learning Engineer III

Pittsburgh, PA · On-site

$111K - $133K/yr

They are seeking a Senior Machine Learning Engineer to develop and optimize machine learning models aimed at enhancing patient care and operational efficiency in hospital settings. Responsibilities ...

Berkadia

Senior Engineer - Machine Learning

Ambler, PA · Hybrid

$100K - $138K/yr

As a Senior Engineer, Machine Learning at Berkadia, you'll be at the forefront of applying cutting-edge machine learning and generative AI to redefine how the commercial real estate industry operates.

Berkadia

Senior Engineer - Machine Learning

Ambler, PA · On-site

$100K - $138K/yr

As a Senior Engineer, Machine Learning at Berkadia, you'll be at the forefront of applying cutting-edge machine learning and generative AI to redefine how the commercial real estate industry operates.

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Senior Machine Learning Ops Engineer information

What are the key skills and qualifications needed to thrive as a senior machine learning ops engineer?

To thrive as a Senior Machine Learning Ops Engineer, you need expertise in machine learning, software engineering, cloud platforms, and experience with CI/CD pipelines, often supported by a computer science degree or equivalent experience. Proficiency with tools like Docker, Kubernetes, TensorFlow, PyTorch, and cloud services such as AWS, GCP, or Azure is typically required, along with familiarity with MLOps frameworks. Strong problem-solving, collaboration, and communication skills help you work effectively with cross-functional teams and manage complex ML model deployments. These skills are essential to ensure reliable, scalable, and efficient deployment of machine learning models in production environments.

What are some common challenges faced by senior machine learning ops engineers when deploying models to production?

Senior Machine Learning Ops Engineers often encounter challenges such as ensuring model reproducibility, managing model versioning, and automating deployment pipelines for scalability. Another key challenge is monitoring model performance and data drift in production, which requires robust logging and alerting systems. Collaborating closely with data scientists, software engineers, and IT teams is essential to address these challenges and maintain a stable, efficient ML infrastructure.

What is the difference between Senior Machine Learning Ops Engineer vs Data Engineer?

AspectSenior Machine Learning Ops EngineerData Engineer
CredentialsExperience with ML frameworks, cloud platforms, scripting, and DevOps toolsStrong SQL, ETL, database, and programming skills, often with cloud experience
Work EnvironmentFocus on deploying, monitoring, and maintaining ML models in productionDesigning and building data pipelines and infrastructure for data processing
Industry UsageCommon in AI/ML-focused companies, tech firms, and data-driven organizationsWidespread across industries for data management and analytics

While both roles involve working with data and cloud platforms, the Senior Machine Learning Ops Engineer specializes in deploying and maintaining machine learning models, whereas the Data Engineer focuses on building data pipelines and infrastructure. Understanding these distinctions helps in choosing the right career path or job search focus.

What is a senior machine learning ops engineer?

Senior Machine Learning Ops (MLOps) Engineers are experienced professionals who design, build, and maintain the infrastructure and tools needed to deploy, monitor, and scale machine learning models in production environments. They work at the intersection of data science, software engineering, and DevOps to ensure ML models are robust, reliable, and secure. Their responsibilities often include automating model training pipelines, managing cloud resources, implementing CI/CD for ML, and ensuring model reproducibility. Senior MLOps Engineers also mentor junior staff and help define best practices for the organization’s ML workflow.

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For Senior Machine Learning Ops Engineer jobs in Pennsylvania, the most frequently searched job titles are:

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Cities in Pennsylvania with the most Senior Machine Learning Ops Engineer job openings:

Senior Machine Learning Ops Engineer jobs near you

Senior Machine Learning Research Scientist - SAIL

Software Engineering Institute | Carnegie Mellon University

Pittsburgh, PA • On-site

$95K - $121K/yr

Full-time

Re-posted 26 days ago

Job description

Job Summary:
Carnegie Mellon University is a leading research institution focused on advancing artificial intelligence and machine learning. They are seeking a Senior Machine Learning Research Scientist to conduct research on AI vulnerabilities and develop strategies to secure AI systems against adversaries.
Responsibilities:
• build real-world, mission-scale AI capabilities through solving practical engineering problems
• discover and define the processes, practices, and tools to support operationalizing AI for robust, secure, scalable, and human-centered mission capabilities
• prepare our customers to be ready for the unique challenges of adopting, deploying, using, and maintaining AI capabilities
• identify and investigate emerging AI and AI-adjacent technologies that are rapidly transforming the technology landscape
• conduct and lead novel research in applied machine learning and artificial intelligence
• work with and lead interdisciplinary teams to turn research results into prototype operational capabilities for government customers and stakeholders
• work with the leadership team and colleagues to plan, develop, and carry out an overall research strategy, and to influence the national research agenda regarding future technology
• actively participate on teams of software developers, researchers, designers, and technical leads
• build relationships and collaborate with researchers, government customers, and other stakeholders to understand challenges, needs, possible solutions, and research directions
• contribute to improving the overall technical capabilities of the Division by mentoring and teaching others, participating in design (software and otherwise) sessions, and sharing insights and wisdom across the SEI AI Division
Qualifications:
Required:
• A bachelor’s degree in computer science, statistics, machine learning, electrical engineering, or related discipline with ten (10) years of experience; OR MS in the same fields with eight (8) years of experience; OR PhD in with five (5) years of experience
• Willingness to work onsite at an SEI facility 5 days per week.
• Be able to obtain and maintain an active Department of War security clearance.
• Willing to travel up to 25% of the time to locations outside of your home location. Travel sites include SEI offices in Pittsburgh and Washington, D.C., sponsor sites, and conferences.
• Comprehensive knowledge of machine learning; previous experience in adversarial machine learning preferred but not required
• A track record of conducting research and applying scientific methods to solve difficult problems
• Experience leading research projects in novel areas with limited previous work to build upon
• Ability to work with leadership to plan, develop, and deliver an overall research strategy
• Strong written and verbal communication skills; ability to convey complex technical ideas in a layperson’s terms
• Proficiency in writing funding proposals or pitching ideas for new research projects
• Ample experience with publishing written or technical artifacts showcasing your work
• Strong collaboration skills for working with colleagues and sponsors
• Willingness to guide and mentor junior team members
Preferred:
• Previous experience in adversarial machine learning
Company:
We conduct cutting-edge research and development that accelerates the transition of technology to the Department of War (DoW), delivering measurable impact in support of the national security mission. Founded in 1984, the company is headquartered in Pittsburgh, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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