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Machine Learning Engineer- Hybrid
Machine Learning Engineer- HybridVITS Consulting • Saint. Paul, MN, United States
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Machine Learning Engineer- Hybrid

Machine Learning Engineer- Hybrid

VITS Consulting • Saint. Paul, MN, United States
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Position Title : Machine Learning Engineer- Hybrid

W2 Role - St. Paul, Minnesota

Primary Responsibilities :

  • Lead the design and development of ML pipelines for advanced AI algorithms and ML models to solve complex problems across diverse business domains.
  • Collaborate on development of ML architecture and implement robust, efficient, and scalable AI systems that integrate seamlessly with existing infrastructure and platforms.
  • Collaborate with research scientists, data scientists, and software engineers to translate research findings into practical, scalable AI solutions.
  • Evaluate and experiment with emerging AI technologies, frameworks, and methodologies to stay at the forefront of innovation. Provide technical guidance and mentorship to junior team members, fostering a culture of continuous learning and growth.
  • Collaborate with stakeholders to understand requirements, gather feedback, and iterate on AI solutions to ensure alignment with business objectives.
  • Deploy, test, and optimize ML models and data pipelines in production environments.
  • Perform model tuning, prompt tuning, and other ML optimization processes alongside other technical experts to maximize the mission impact of the AI product.
  • Participate in the delivery, evaluation, and maintenance of enterprise products, ensuring they meet high-quality standards.

Skills Needed : Qualifications :

  • Advanced degree (Master's or Ph.D.) or equivalent industry experience in Computer Science, Machine Learning, or related fields.
  • 5+ years of experience in a similar role in a production environment.
  • Experience working with large scale datasets and building ETL pipelines using Spark, Kubeflow, StreamSets, etc.
  • Hands-on experience with cloud computing platforms such as AWS.
  • Strong proficiency in Python and experience with NLP techniques, resources, and methodologies such as Scikit-learn, TensorFlow, PyTorch, HuggingFace, Comprehend, XGBoost, LangChain, etc.
  • Experience integrating machine learning models and data-driven algorithms into larger system architectures that involve pieces like Flask, ElasticSearch, PostgreSQL, IBM MQ, Apache Kafka, etc.
  • Experience with iterative development processes, thriving in dynamic and agile environments.
  • Ability to own ML delivery tasks end-to-end with little to no direct support. Hands-on experience in deploying machine learning models into production environments.
  • Strong understanding of software design patterns, principles, architecture, and operations.
  • Strong communication skills and the ability to collaborate effectively with business partners, vendors, end users, and cross-functional teams
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