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Data Scientist/ML Engineer
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IPS Technology Services
Dearborn, MI (In Person)
Full-Time
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Job Description
Job Description Machine Learning Engineer Location:
Resources will be in office 4 days a week in Dearborn, MI Job type: Direct hire - Full timeRequired Qualifications:
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field
- Strong Python programming experience (backend development, APIs, automation)
- Experience deploying ML models in production environments
- Experience with ML frameworks (Scikit-learn, TensorFlow, PyTorch)
- Hands-on experience with LLMs, prompt engineering, and Generative AI
- Experience working with cloud platforms (GCP and/or AWS)
- Strong understanding of SDLC, version control, testing, and deployment practices
- Excellent analytical, communication, and problem-solving skills
- Ability to work in fast-paced, agile environments
Primary Skills:
Python, Machine Learning, Data Science, GCP, BigQuery Experience Requirements:
- Engineer Level 3
- 6+ years of IT experience
- 4+ years of development experience
- Experience with 2 programming languages or advanced proficiency in 1
Preferred Experience:
- Agentic AI systems, multi-step workflows, autonomous agents, tool-calling architectures
- Frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, etc.
- MLOps tools: MLflow, Airflow, Vertex AI, SageMaker, Kubeflow, etc.
- Docker and Kubernetes
- Vector databases, embeddings, RAG, semantic search
- Large-scale enterprise data systems and data lakes
- AI system optimization (performance, cost, scalability)
- AI product or analytics platform development
Additional Qualifications:
- Self-starter with ability to work independently
- Strong communicator across technical and non-technical teams
- Collaborative and team-oriented
- Innovative mindset with strong problem-solving ability
- Results-driven and focused on production impact
Education:
- Bachelor's Degree required
Additional Information:
- Strong experience required in production-grade AI systems, APIs, and cloud-native Deployments I'm interested