840 Engineering Technologist jobs in Stockbridge,GA

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ASIC Engineer

Falcomm

Atlanta, GA 30349

New, Posted 18 hours ago

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Senior Reliability Engineer

Anduril Industries

Atlanta, GA 30349

~ 39 min OnsiteHealth Insurance

Minimum of 8 years experience as a Reliability Engineer, Design/Development Engineer, or Test Engineer
B.S. Degree in Mechanical Engineering, Aerospace Engineering, Systems Engineering, or equivalent technical discipline
Experience with safety-critical hardware & software systems in the defense or aerospace industry
Experience or familiarity with MIL-STD-810, MIL-HDBK-217, MIL-STD-461, MIL-STD-516C, and MIL-STD-1629
Experience setting up a Reliability Engineering framework for a product or program, including support of production testing, field testing, data acquisition, and data analysis
Expertise in reliability analysis techniques, including FMEA/FMECA, predictive modeling, Weibull analysis, and Fault Tree Analysis
Experience with generating qualification testing requirements and executing tests to proactively characterize product behavior and performance
Failure investigation/analysis experience with proven track record of solving problems and preventing reoccurrence
Design Review Experience (PDR, CDR, MRR) and confidence in presentation skills across all levels of leadership
Eligibility to obtain/maintain a U.S. Secret clearance, as required

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Toolchain / Digital Design Engineer

Southeastern Cyber LLC

Atlanta, GA 30332

Flexible Schedule

DiversityJobs

Senior Software Engineer

CIENA

Atlanta, GA 30349

Flexible Schedule

New, Posted 9 hours ago

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Senior Java/ Machine Learning Engineer (Supply Chain & Fulfillment)

Marathon TS

Atlanta, GA 30349

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Design Engineer

Kelly Services

Atlanta, GA 30309

New, Posted 1 day ago

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Nuclear Engineer

U.S. Navy

Morrow, GA 30260

New, Posted 1 day ago

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iHire

Controls Engineer

Geiger

Atlanta, GA 30301

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Machine Learning Lead Engineer

Cox Automotive

Lake City, GA 30260

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.