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
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 10105282
- Position Id: 888344
- Posted 3 hours ago
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