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Mlops Junior Jobs in Springfield, MA (NOW HIRING)

Virtusa Corporation

GenAI Lead

Hartford, CT · On-site

$55.75 - $76.50/hr

... junior engineers and provide technical leadership on best practices in ML model development, optimization, and MLOps Collaborate cross functionally with product owners data scientists and business ...

The Hartford

Senior AI Machine Learning Engineer

Hartford, CT · Hybrid

$123K - $162K/yr

... MLOps) services for the Customer Operations Data Science team. The Hartford is developing ... Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable ...

The Hartford

Sr AI Machine Learning Engineer

Hartford, CT · Hybrid

$117K - $175K/yr

... MLOps) services for the Global Specialty Applied AI team. The Hartford is developing ... Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable ...

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Mlops Junior information

See Springfield, MA salary details

$7

$26

$47

How much do mlops junior jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for mlops junior in Springfield, MA is $26.86, according to ZipRecruiter salary data. Most workers in this role earn between $16.30 and $33.08 per hour, depending on experience, location, and employer.

What is an MLOps junior?

MLOps Junior roles focus on supporting the deployment, maintenance, and monitoring of machine learning models in production environments. As a junior professional, you typically assist in automating workflows, managing data pipelines, and collaborating with data scientists and engineers. Responsibilities often include configuring cloud resources, setting up CI/CD pipelines, and ensuring models run smoothly after deployment. It's an entry-level position that helps bridge the gap between data science and operations, providing hands-on experience with machine learning infrastructure.

What are the key skills and qualifications needed to thrive as an MLOps junior?

To thrive as an MLOps Junior, you need a solid understanding of machine learning principles, programming in Python, and knowledge of software development practices, often supported by a degree in computer science or a related field. Familiarity with cloud platforms (such as AWS or Azure), containerization tools (like Docker), CI/CD pipelines, and version control systems (like Git) is typically required. Strong problem-solving, collaboration, and a willingness to learn stand out as soft skills in this role. These skills and qualities are crucial for efficiently deploying, maintaining, and scaling machine learning models in real-world production environments.

What are some common challenges faced by a junior MLOps professional in their first year, and how can they overcome them?

As a Junior MLOps professional, one of the main challenges is bridging the gap between data science and engineering practices, particularly when deploying machine learning models to production. You may encounter issues like automating model pipelines, managing dependencies, and ensuring reproducibility. Collaborating closely with data scientists, software engineers, and DevOps teams is essential for learning best practices and troubleshooting problems efficiently. Proactively seeking mentorship, participating in code reviews, and familiarizing yourself with popular MLOps tools (such as Docker, Kubernetes, and CI/CD platforms) can greatly accelerate your growth and confidence in the role.

What is the difference between Mlops Junior vs Data Engineer?

AspectMlops JuniorData Engineer
Required CredentialsBasic understanding of ML workflows, some certifications preferredDegree in Computer Science or related field, certifications in data management
Work EnvironmentCollaborates with data scientists and ML engineers in tech companiesWorks on data pipelines, storage, and processing systems in various industries
Industry UsageEmerging role in AI/ML teams, startups, and tech firmsEstablished role across finance, healthcare, tech, and more

The comparison shows that Mlops Junior and Data Engineer roles share some technical foundations but differ mainly in focus. Mlops Junior emphasizes deploying and maintaining ML models, while Data Engineers focus on building data infrastructure. Both roles are vital in data-driven organizations, with Mlops Junior often working closely with Data Engineers to ensure smooth ML operations.

Is MLOps a good career choice in 2026?

MLOps Junior roles are expected to remain in demand in 2026 due to the growing adoption of machine learning and AI across industries. These roles typically require skills in cloud platforms, automation, and tools like Docker and Kubernetes, making them a promising career path for those interested in AI deployment and infrastructure. Continuous learning and certification in relevant technologies can enhance job prospects in this field.

Is MLOps in high demand?

MLOps junior roles are in high demand as organizations increasingly adopt machine learning and AI solutions. These positions require skills in cloud platforms, automation, and tools like Docker and Kubernetes, reflecting the growing need for efficient deployment and management of ML models across industries.

What job categories do people searching Mlops Junior jobs in Springfield, MA look for?

The top searched job categories for Mlops Junior jobs in Springfield, MA are:

What cities near Springfield, MA are hiring for Mlops Junior jobs?

Cities near Springfield, MA with the most Mlops Junior job openings:

Mlops Junior jobs near you
Infographic showing various Mlops Junior job openings in Springfield, MA as of June 2026, with employment types broken down into 94% Full Time, 5% Part Time, and 1% Temporary. Highlights an 76% Physical, 4% Hybrid, and 20% Remote job distribution, with an average salary of $55,872 per year, or $26.9 per hour.

GenAI Lead

Virtusa Corporation

Hartford, CT • On-site

$55.75 - $76.50/hr

Full-time

Posted 10 days ago

Job description

Lead the design development and deployment of machine learning and GenAI models in collaboration with AI Architects, Cloud Engineers and CRM Development Teams
Architect end to end ML pipelines from data preparation and model training to deployment and monitoring - ensuring scalability efficiency and compliance
Evaluate and fine tune state of the art models eg Gemini GPT 4 and other LLMs and integrate them into enterprise systems such as Salesforce
Guide retraining efforts to maintain model performance fairness and ethical standards
Mentor junior engineers and provide technical leadership on best practices in ML model development, optimization, and MLOps
Collaborate cross functionally with product owners data scientists and business stakeholders to translate business needs into AI solutions
Ensure AI governance and ethics by monitoring for bias ensuring data privacy compliance and adhering to responsible AI principles
Stay ahead of industry trends tools and research to continuously innovate and improve AI capabilities within the organization.
Document architectures workflows and model lifecycles for transparency reproducibility and audit readiness.
Required Qualifications
Bachelors degree in Computer Science Information Technology Computer Engineering or related field (advanced degree preferred
Proven experience 5 8 years in Machine Learning Engineering or AI Solution Design with demonstrated leadership or tech lead responsibilities
Deep expertise in Generative AI LLMs eg Gemini, GPT 4 Claude etc and traditional ML NLP Deep Learning techniques.
Proficiency in Python and related ML frameworks eg TensorFlow PyTorch Hugging Face LangChain).
Strong experience with cloud platforms (preferably Google Cloud Platform but AWS or Azure also considered).
Demonstrated ability to architect scalable ML systems and integrate AI capabilities into enterprise platforms eg Salesforce
Excellent analytical, problem-solving, and troubleshooting skills
Strong collaboration and communication abilities with a track record of leading technical teams
Preferred / Nice to Have
Hands-on experience with CRM platforms like Salesforce
Understanding of data privacy, security, and ethical AI practices
Experience mentoring or training teams in AI ML concepts and implementation
Strong project management or agile delivery experience
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About Virtusa

Sourced by ZipRecruiter

We are builders, makers, and doers with the technical skills and domain expertise to transform your business at scale and speed without disruption. Our unique Engineering First approach blends deep industry expertise and empowered, agile teams, to create holistic solutions that seamlessly move the business forward. We help clients engage with new technology paradigms to creatively build solutions that drive them to the forefront of their industries.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Westborough, MA, US

Year founded

1996

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