Job Description Seeking a new job opportunity in the Minneapolis area? Don't miss this role. Dahl Consulting is currently partnering with a leader in the retail industry. We work one-on-one with great candidates to help connect them with local employment opportunities. This Company is hiring a Lead Machine Learning Engineer for a contract position. Interested? Get more details below.
Contract Duration: 5-months
Worksite Location: Brooklyn Park, MN (Hybrid)
Compensation: $60.00-$82.00 per hour
What you'll do as the Lead Machine Learning Engineer: - Develop and deploy end-to-end machine learning solutions, including data pipelines, model optimization, deployment strategies, and API design
- Collaborate closely with data scientists, software engineers, and product managers to understand business needs and deliver scalable ML solutions
- Build and optimize models using frameworks such as PyTorch, TensorFlow, XGBoost, scikit-learn, and ONNX
- Leverage cloud-based ML platforms including Vertex AI, Azure ML, or SageMaker to deploy and manage models at scale
- Utilize distributed training frameworks like Spark, Ray, or TensorFlow Distribute for high-performance model training
- Implement model serving using platforms such as TorchServe, TensorFlow Serving, or FastAPI
- Design and maintain CI/CD pipelines for automated ML model testing, validation, and deployment
- Work with big data technologies including Kafka and Spark to integrate real-time and large-scale data workflows
- Mentor junior team members in machine learning skills and contribute to their professional growth
- Effectively communicate data-driven insights through visualizations, storytelling, and clear documentation
What you'll bring to the Lead Machine Learning Engineer role: - Bachelor's degree in a quantitative discipline (Science, Technology, Engineering, Mathematics) or equivalent work experience
- Master's degree in Computer Science, Applied Mathematics, Statistics, Physics, or equivalent industry experience
- 5+ years of hands-on experience in developing, optimizing, and deploying machine learning models
- Proficiency in Python and either PySpark or Scala
- Strong knowledge of modern ML frameworks (e.g., PyTorch, TensorFlow, XGBoost, scikit-learn, ONNX)
- Experience with cloud-based ML services (e.g., Vertex AI, Azure ML, SageMaker)
- Familiarity with distributed computing and model training frameworks (Spark, Ray, TensorFlow Distribute)
- Experience building APIs and using ML model serving tools (TorchServe, TensorFlow Serving, FastAPI)
- Understanding of big data tools such as Kafka and Spark
- Ability to create and maintain CI/CD pipelines for ML deployments
- Strong communication and collaboration skills, with a proven ability to work across cross-functional global teams
Take the first step on your new career path. To submit yourself for consideration for this role, simply click the apply button and complete our mobile-friendly online application. Once we've reviewed your application details, a recruiter will reach out to you with next steps. For questions or more information about this role, please call our office at .
As an equal opportunity employer, Dahl Consulting welcomes candidates of all backgrounds and experiences to apply. If this position sounds like the right opportunity for you, we encourage you to take the next step and connect with us. We look forward to meeting you.
Dahl Consulting is proud to offer a comprehensive benefits package to eligible employees that will allow you to choose the best coverage to meet your family's needs. For details, please review the DAHL Benefits Summary:
Dahl Consulting is proud to offer a comprehensive benefits package to eligible contract employees that will allow you to choose the best coverage to meet your family's needs. For details, please review our Benefits Summary:
Dahl Consulting is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other applicable legally protected characteristics.
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