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Machine Learning Technical Project Manager Jobs in Hale, MI

Ashley Phibbs- Technical Project Manager Work Schedule : Full Time Summary: The ACC Lead will assist with the creation and up-keep of SOPs, stay informed about AMOS improvements, be the first line of ...

Data Processor Supervisor and Project Manager ESSENTIAL DUTIES AND RESPONSIBILITIES: Duties and ... High school graduate; some college and/or technical school desirable. Must be able to copy, file.

Data Processor Supervisor and Project Manager ESSENTIAL DUTIES AND RESPONSIBILITIES: Duties and ... High school graduate; some college and/or technical school desirable. Must be able to copy, file.

Assign work activities and projects; monitors workflow; reviews and evaluates work products ... Create and manage technical budgets * Ensure that role-driven operational key performance indicator ...

Assign work activities and projects; monitors workflow; reviews and evaluates work products ... Create and manage technical budgets * Ensure that role-driven operational key performance indicator ...

Advanced understanding of Learning Management Systems, preferred. * Strong knowledge of ... Excellent time management and project management skills. * Ability to communicate effectively ...

This position serves (for this function across all laboratory sites) as a technical resource person ... Responsible to maintain high quality, high value laboratory services, through ongoing learning and ...

Two Year College Degree or applicable Technical Training and Certification is preferred ... Has no supervisory responsibilities; manages own workload * Must be able to read metric and ...

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Machine Learning Technical Project Manager information

See Hale, MI salary details

$39K

$105.3K

$161.3K

How much do machine learning technical project manager jobs pay per year?

As of Aug 13, 2026, the average yearly pay for machine learning technical project manager in Hale, MI is $105,255.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,000.00 and $120,500.00 per year, depending on experience, location, and employer.

What is the difference between Machine Learning Technical Project Manager vs Data Scientist?

AspectMachine Learning Technical Project ManagerData Scientist
Required CredentialsBachelor's or Master's in CS, Engineering, or related; PMP or Agile certificationsBachelor's, Master's, or PhD in Data Science, Statistics, or related
Work EnvironmentProject teams, cross-functional collaboration, managing ML projectsData analysis, model development, research-focused
Employer & Industry UsageTech companies, AI startups, R&D departmentsTech firms, finance, healthcare, research institutions
Common Search & Comparison IntentUnderstanding project management roles in MLUnderstanding data analysis and modeling roles

The main difference between a Machine Learning Technical Project Manager and a Data Scientist lies in their focus. The project manager oversees ML projects, coordinating teams and ensuring timely delivery, while the data scientist focuses on analyzing data, building models, and deriving insights. Both roles often collaborate but serve distinct functions within ML initiatives.

Staff AI/ML Engineer (Large Language Model) (TS/SCI) {S}

Danbury Mission Technologies

Lewiston, MI • On-site

Full-time

Re-posted 12 days ago


Job description

Job Summary:
Danbury Mission Technologies is an advanced technologies company serving the U.S. military and intelligence community. The Staff AI/ML Engineer will lead the development of Agentic AI capabilities and other LLM based capabilities for mission management applications.
Responsibilities:
• Lead and mentor a multidisciplined team consisting of developers and researchers to implement machine learning algorithms to solve a broad set of challenges for our various customers
• Lead and mentor a multidisciplinary team delivering advanced AI/ML solutions
• Apply LLMs to complex domain-specific problems and operational workflows
• Adapt and fine-tune foundation models for specialized use cases
• Design and implement retrieval-augmented generation (RAG) systems and semantic search architectures
• Build production-grade LLM applications and agentic systems
• Deploy scalable AI solutions across cloud, on-prem, and hybrid environments
• Analyze large, multi-modal datasets to extract meaningful features and actionable insights
• Translate emerging research into applied, mission-relevant capabilities
• Communicate technical strategy, status, and risks to internal and external leadership
Qualifications:
Required:
• B.S. in machine learning, computer science, mathematics, or related fields
• 8+ years of experience, preferably in software development or as a data scientist with 2+ years of building LLM applications using some of the following: Fine-tuning foundational models, Steering Techniques (e.g Sparse auto encoders, representation tuning), Building adapters to use foundational models (e.g. PEFT, llama factory), Prompt engineering techniques / Inference time techniques (e.g. chain of thought, tree of thoughts, etc.), Using Retrieval Augmented Generation techniques to populate and query vector databases (e.g. Weaviate, pinecone, pgvector), Using LLM Frameworks (e.g. LangChain, DSPy, Microsoft Agent Framework), Using AI APIs ( e.g AWS Bedrock, OpenAI), Using LLM deployment frameworks (eg llama.cpp, vllm, tgi), Developing UIs with ReAct
• Experience leading an interdisciplinary team of researchers and software developers and working with a program manager to define project scope and schedule to ensure we meet project milestones as defined by our customers
• Experience with Python and data science / machine learning libraries (e.g. NumPy, Pandas, Polars, scikit-learn, etc.)
• Experience contributing on a team using version control (e.g. git, GitLab, Bitbucket)
• Active TS/SCI U.S. Government Security Clearance
Preferred:
• M.S. or PhD in machine learning, computer science, mathematics, or related fields
• Experience leading an interdisciplinary team of researchers and software developers
• Experience with any of the following: Large Language Models and experience identifying ways to incorporate them into new domains and applications
• Applying Transformer-based architectures to domains in other areas outside of Natural Language Processing (NLP) such as computer vision
• Natural Language Processing algorithms such as BERT
• Reinforcement learning and familiarity with Gymnasium Gym, OpenEnv, TorchRL, RLlib, and Stable Baselines
• Applying clustering algorithms and/or deep neural networks to real life problems
• Implementing tracking and pattern-of-life algorithms
• Experience with GenAI Ops techniques (e.g. LLM-as-a-judge) and frameworks (e.g. LangFuse, MLFlow, Arize Phoenix)
• Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
• Experience with Linux
• Experience with CUDA and Python libraries such as CuPy, Numba, CuSignal, CuDF, etc.
• Familiarity with using AWS cloud computing resources such as EC2, S3, Lambda, etc.
• Experience with any of the following additional languages: Java, C++, Rust, Go, and/or C#
• Experience in application deployment, virtualization, and containerization (e.g. Podman, Docker, Kubernetes, Rancher)
• Experience shaping and writing proposals
• Adjudicated Counter Intelligence or Full Scope Polygraph
Company:
This page is no longer active. Visit ARKA.org. Founded in , the company is headquartered in Danbury, Connecticut, US, , with a team of 501-1000 employees. The company is currently Late Stage.