546 Mechatronics Engineer jobs in Newnan,GA

HS Diploma or GED
On the job experience of 1-3 years in manufacturing environment
Must be able to follow instructions, read and interpret blue prints
Must be able to work in a team environment
Only US persons (US citizen, US naturalized citizen, US permanent resident, holder of US approved political asylee or refugee status) may be considered for this role
Background investigation and drug screen in accordance with company policy and applicable federal and state regulations
Authorized to work in the U.S. (as evidenced by Form I-9 information)

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Senior Manufacturing Engineer, Digital Tools

Anduril Industries

Atlanta, GA 30349

~ 47 min OnsiteHealth Insurance

Bachelor's degree in Manufacturing Engineering, Industrial Engineering, Software Engineering, User Experience Design, or related field.
8+ years of experience in a digital manufacturing environment, including familiarity with MES, ERP, and PLM systems and how they interface with each other and with operations.
High sense of user empathy and the ability to manage and communicate with stakeholders.
Ability to quickly understand current operations and potential issues on the product line and can speak the language.
Strength working with manufacturing leadership to conceptualize solutions and gain / understand requirements
Excellent communication and presentation skills, capable of conveying complex information in an understandable manner.
Ability to work collaboratively in a team environment and lead cross-functional projects.
Adept at managing multiple priorities in a fast-paced manufacturing environment.
Must be a U.S. Person due to required access to U.S. export controlled information or facilities

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Nuclear Engineer

US Navy

Grantville, GA 30220

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Avionics Manufacturing Engineer

Hermeus

Atlanta, GA 30349

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Director, AI Engineer

KPMG

Atlanta, GA 30349

~ 47 min OnsiteHealth InsuranceRetirement Benefit

Minimum eight years of recent experience in AI/ML, data analytics, and cloud technology, including leadership roles in consulting or technology organizations; AI certifications (for example: Professional AI Architect, Machine Learning Engineer) or equivalent are a plus
Advanced degree from an accredited college or university in computer science, data science, engineering, or related field preferred; minimum of a Bachelor's degree from an accredited college or university is required
Deep knowledge and hands-on experience with Microsoft, AWS, and/or Google Cloud's AI ecosystem (including agent build functionality) to design and orchestrate intelligent multi-agent systems such as chatbots and virtual assistants that handle complex, dynamic tasks and conversations
Proficient in architecting and implementing AI-powered workflow solutions using Microsoft, AWS, or Google Cloud services (For example: Foundry, Bedrock, Vertex AI), with capabilities in defining blueprints and technical requirements for scalable, automated systems with expertise in agentic AI and automation
Skilled in designing multi-agent conversational AI systems integrated with enterprise applications (CRM, ERP), enhancing customer engagement through smart chatbots and virtual agents to improve user experience and operational efficiency; experienced in conversational AI integration
Deep understanding of scaling AI-driven solutions, ethical AI, and MLOps practices for maintaining models; ability to bring industry consulting insights with a balance of technical and business acumen to deliver strategic, value-driven AI solutions; In-depth knowledge of AI orchestration and best practices
Travel as needed
Applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future; KPMG LLP will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa)

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Machine Learning Lead Engineer

Cox Automotive

Fairburn, GA 30213

~ 22 min OnsitePaid Time Off

Applicants must currently be authorized to work in the United States for any employer without current or future sponsorship. No OPT, CPT, STEM/OPT or visa sponsorship now or in future.
Bachelor's degree in a related discipline and 6 years' experience in Machine Learning; or a different combination, such as a master's degree and 4 years' experience; a Ph.D. and 1 years' experience in a related field; or 18 years' experience in a related field with no degree
Minimum of 6 years of experience as a Machine Learning Engineer or equivalent
Deep expertise in multiple ML domains and familiarity with emerging research areas
Strong experience in technology evaluation, competitive analysis, and strategic planning
Comfortability with non-deterministic systems
Product background- understand how to prioritize, collaborate across teams, manage dependencies with others, set strategy
Experience in Rally, Jira or similar tools
Skilled in analytical thinking, consulting, requirements analysis, system and technology integration and technology savvy.
Skilled in collaborating with intent, communicating with impact, developing trust, driving innovation and striving for excellence.
Proven track record of leading innovative projects from concept to proof-of-concept
Demonstrated success in knowledge sharing and thought leadership (publications, speaking, etc.)
Experience building and leading high-performing research or innovation teams
Excellent communication skills for technical and executive audiences
Strong network within the ML research community
Experience with research collaboration and partnership development
Proficiency in AI development tools (GitHub Copilot, Claude, GPT-4) for ML development with ability to validate AI outputs for production readiness.
Understanding of agentic frameworks (AWS AgentSquad, AWS Strands, LangChain, agent patterns) with progression from basic configuration to custom enterprise system design.
Knowledge of AI ethics, responsible AI practices, and governance frameworks for business-critical ML deployment.
Ability to leverage AI like Co-Pilot for technical communication to stakeholders and cross-functional collaboration.
Commitment to continuous learning in AI-augmented data science and responsible AI use.