Machine Learning Engineer II

Help develop machine learning solutions that support real products and applications. As a Machine Learning Engineer II, you’ll work across algorithm development, data pipelines, model validation, and production deployment while helping turn promising ideas into dependable technical solutions. This role combines hands-on programming with testing, documentation, and collaboration across engineering teams.

You’ll be a key contributor on projects that move machine learning from concept to implementation. The ideal candidate has enough experience to work independently on assigned initiatives, but is still excited to learn, explore new approaches, and collaborate with others when challenges arise. From designing proof-of-concept solutions to monitoring deployed models, you’ll gain broad exposure to the machine learning lifecycle.

Required Skills & Experience

· 3–5 years of related experience after completing a bachelor’s degree, or a recent master’s degree

· Experience implementing, refining, and validating machine learning or deep learning algorithms

· Strong programming and software development skills

· Familiarity with Python, Java, Scala, or similar programming languages

· Experience designing or supporting data pipelines for ingestion, validation, cleaning, and monitoring

· Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, or a related technical discipline—or equivalent industry experience

Desired Skills & Experience

· Experience with data mining or statistical analysis tools

· Experience deploying and monitoring machine learning models

· Knowledge of Kafka, Spark, Docker, or similar data and cloud technologies

· Experience designing proof-of-concept solutions or contributing to technical studies

· Familiarity with model testing, accuracy evaluation, case studies, or performance reporting

· Experience collaborating with teams outside of an immediate work group

What You Will Be Doing

· Implement, refine, and validate machine learning algorithms for products and applications

· Design and develop data pipelines for data ingestion, validation, cleaning, and monitoring

· Train models, evaluate accuracy, and support the deployment of validated models into production

· Design proof-of-concept solutions and contribute to future product development efforts

· Test and evaluate solutions through case studies, technical reviews, and reporting

· Collaborate with cross-functional teams to address technical issues and support project delivery

Tech Breakdown

· 30% Machine Learning Algorithm and Model Development

· 25% Data Pipeline and Cloud Technologies

· 20% Model Training, Validation, and Deployment

· 15% Proofs of Concept, Testing, and Evaluation

· 10% Documentation, Collaboration, and Technical Support

Daily Responsibilities

· Develop and refine machine learning algorithms and models

· Build, test, and monitor data pipelines

· Review model accuracy, performance, and production results

· Support model deployment and ongoing monitoring activities

· Contribute to proof-of-concept projects, case studies, and technical evaluations

· Prepare requirements, test results, reports, presentations, and other technical documentation

· Work with engineering and technical teams to resolve project issues and improve solutions

As part of our promise to talent, Kelly supports those who work with us through a variety of benefits, perks, and work-related resources. Kelly offers eligible employees voluntary benefit plans including medical, dental, vision, telemedicine, term life, whole life, accident insurance, critical illness, a legal plan, and short-term disability.

As a Kelly employee, you will have access to a retirement savings plan, service bonus and holiday pay plans (earn up to eight paid holidays per benefit year), and a transit spending account. In addition, employees are entitled to earn paid sick leave under the applicable state or local plan.

Click here for more information on benefits and perks that may be available to you as a member of the Kelly Talent Community.