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Junior Ai Machine Learning Python Jobs in Michigan

... Python, Java, C#, JavaScript) * Define and enforce coding standards, best practices, and design ... AI / Machine Learning Development * Design, develop, and train machine learning and deep learning ...

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $160K/yr

The Tech This is some of the most interesting applied AI work happening today. Our internal ... Proficiency in Python and comfort reading and debugging an existing codebase. * Curiosity about ...

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... Adapts instruction using Python with scikit-learn, Jupyter notebooks, and real-world data sets to ...

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... Adapts instruction using Python with scikit-learn, Jupyter notebooks, and real-world data sets to ...

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... Adapts instruction using Python with scikit-learn, Jupyter notebooks, and real-world data sets to ...

... Machine learning Positions Preferred SKILLS Associate or Bachelors degree or Masters degree in ... Gen AI, LLM, Sagemaker, Python, Computer Vision, data visualization tools Candidates lacking ...

Machine Learning Engineer

Dearborn, MI

$105K - $126K/yr

They automate and optimize the end-to-end ML and Gen AI model lifecycle using expertise in ... Proficiency in Python programming. * Solid experience with SQL for data manipulation and querying.

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Junior Ai Machine Learning Python information

What are the key skills and qualifications needed to thrive as a Junior AI Machine Learning Python Engineer, and why are they important?

To thrive as a Junior AI Machine Learning Python Engineer, you need a solid understanding of Python programming, statistics, and foundational machine learning concepts, often supported by a degree in computer science or a related field. Familiarity with tools and frameworks like TensorFlow, Scikit-learn, Jupyter Notebooks, and version control systems such as Git is typically required. Strong problem-solving abilities, attention to detail, and effective teamwork skills help individuals excel in collaborative and fast-evolving technical environments. These competencies are crucial for developing robust AI solutions, learning from senior colleagues, and adapting to the rapidly changing landscape of machine learning.

What does a Junior AI Machine Learning Python engineer do?

A Junior AI Machine Learning Python engineer assists in developing, testing, and maintaining machine learning models using Python. They typically work with data preparation, preprocessing, and applying basic algorithms to solve real-world problems. Under the guidance of senior engineers, they help implement solutions, evaluate model performance, and may contribute to the deployment of models into production environments. Their role often includes learning best practices in coding, software development, and collaborating with data scientists and engineers.

What are some typical projects or tasks a Junior AI/Machine Learning Python developer might work on in their first year?

As a Junior AI/Machine Learning Python developer, you can expect to work on tasks such as cleaning and preparing datasets, developing and testing simple machine learning models, and assisting in the implementation of algorithms under the supervision of senior team members. You may also help automate data pipelines, write scripts for data extraction, and contribute to model evaluation and reporting. Collaboration with data scientists, software engineers, and product managers is common, providing valuable learning opportunities and exposure to the full machine learning workflow.

What is the difference between Junior Ai Machine Learning Python vs Data Analyst?

AspectJunior Ai Machine Learning PythonData Analyst
Required SkillsPython, Machine Learning, AI concepts, data preprocessingExcel, SQL, data visualization, basic statistical analysis
CertificationsPython certifications, AI/ML coursesData analysis or visualization certifications
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, marketing departments
Industry UsageDeveloping AI models, machine learning pipelinesInterpreting data, generating reports, supporting decision-making

Junior Ai Machine Learning Python roles focus on developing AI models using Python and machine learning techniques, often in tech-driven environments. Data Analysts primarily interpret data, create visualizations, and support business decisions. While both roles require analytical skills, AI/ML roles demand programming and AI-specific knowledge, whereas Data Analysts focus on data interpretation and reporting.

What are popular job titles related to Junior Ai Machine Learning Python jobs in Michigan? For Junior Ai Machine Learning Python jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Junior Ai Machine Learning Python jobs in Michigan look for? The top searched job categories for Junior Ai Machine Learning Python jobs in Michigan are:
What cities in Michigan are hiring for Junior Ai Machine Learning Python jobs? Cities in Michigan with the most Junior Ai Machine Learning Python job openings:
Machine Learning Engineering Engineer 3

Machine Learning Engineering Engineer 3

Kyyba

Dearborn, MI

Other

Posted 7 days ago


Job description

We are seeking an experienced AI Engineer to design, develop, and deploy intelligent solutions that leverage Machine Learning, Large Language Models (LLMs), and emerging Agentic AI capabilities to transform business processes and drive operational efficiency. This role combines expertise in Data Science, Software Engineering, and MLOps to deliver scalable, production-ready AI systems that generate measurable business value. The ideal candidate will have hands-on experience building and operationalizing AI/ML solutions in enterprise environments, with a strong focus on Generative AI, intelligent automation, and cloud-native architectures. Key Responsibilities Design, develop, and deploy machine learning models, including predictive, optimization, and Generative AI solutions. Build end-to-end AI workflows encompassing data ingestion, feature engineering, model training, deployment, monitoring, and continuous improvement. Develop and implement LLM-powered applications, including Retrieval-Augmented Generation (RAG), prompt orchestration, agentic workflows, and tool integrations. Create scalable APIs and AI services that seamlessly integrate with enterprise applications and business processes. Establish and maintain MLOps practices, including automated training, deployment, monitoring, retraining, and performance management. Ensure AI solutions are reliable, scalable, secure, and optimized for production environments. Collaborate closely with business and technical stakeholders to identify opportunities and translate business challenges into AI-driven solutions. Monitor model performance and implement ongoing enhancements based on business feedback, operational metrics, and evolving requirements. Stay current with advancements in AI, Generative AI, Agentic AI, and MLOps to continuously improve solution capabilities and delivery approaches. Required Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related discipline. Strong programming experience in Python, including backend development, API design, automation, and software engineering best practices. Hands-on experience building, deploying, and supporting machine learning models in production environments. Experience with machine learning frameworks such as Scikit-learn, TensorFlow, and/or PyTorch. Practical experience developing applications using Large Language Models (LLMs), prompt engineering, and Generative AI technologies. Experience building AI solutions on cloud platforms such as GCP and/or AWS. Strong understanding of software development lifecycle, version control, testing, and deployment practices. Excellent analytical, problem-solving, and communication skills. Ability to thrive in a fast-paced, agile environment with evolving priorities and business needs
Skills Required:
Python, Machine Learning, Data Science, GCP, Big Query
Skills Preferred:
N/A
Experience Required:
Engineer 3 Exp: Prac. In 2 coding lang. or adv. Prac. in 1 lang. 6+ years in IT; 4+ years in development Experience designing and implementing Agentic AI solutions, multi-step workflows, autonomous agents, and tool-calling architectures. Experience with AI orchestration frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, or similar technologies. Hands-on experience with MLOps tools and platforms including MLflow, Airflow, Vertex AI, SageMaker, Kubeflow, or equivalent solutions. Experience with containerization and orchestration technologies such as Docker and Kubernetes. Familiarity with vector databases, embeddings, Retrieval-Augmented Generation (RAG), and semantic search architectures. Experience working with enterprise-scale data environments, data lakes, and large datasets. Experience optimizing AI systems for scalability, performance, reliability, and cost efficiency. Experience building AI-powered products, dashboards, analytics solutions, or intelligent automation platforms.
Experience Preferred:
Self-starter with the ability to work independently and navigate ambiguity. Strong communicator capable of engaging both technical and non-technical stakeholders. Collaborative team player who can effectively partner across business and technology functions. Innovative thinker with a passion for applying AI to solve real-world business challenges. Results-oriented mindset focused on delivering practical, scalable, and impactful solutions.
Education Required:
Bachelor's Degree
Additional Information:
4 days in the office Python (advanced), SQL Machine Learning & Deep Learning LLMs, Prompt Engineering, RAG, Embeddings Agentic AI / AI Agents / Tool Calling Vector Databases ML Frameworks: Scikit-learn, TensorFlow, PyTorch MLOps: MLflow, Airflow, CI/CD, model deployment & monitoring Cloud: AWS or GCP Docker, Kubernetes API development (FastAPI / Flask) Data pipelines (ETL), data lakes/warehouses Strong system design & production AI experience


KYYBA logo

About KYYBA

Sourced by ZipRecruiter

About Kyyba: Founded in 1998 and headquartered in Farmington Hills, MI, Kyyba has a global presence delivering high-quality resources and top-notch recruiting services, enabling businesses to effectively respond to organizational changes and technological advances. At Kyyba, the overall well-being of our employees and their families is important to us. We are proud of our work culture which embodies our core values; incorporating value, passion, excellence, empowerment, and happiness, creates a vibrant and productive atmosphere. We empower our employees with the resources, incentives, and flexibility that they need to support a healthy, balanced, and fulfilling career by providing many valuable benefits and a balanced compensation structure combined with career development.

Industry

Recruiting and staffing services

Company size

501 - 1,000 Employees

Headquarters location

Farmington Hills, MI, US

Year founded

1998

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