Staff Machine Learning Engineer

Unlock New Career Opportunities with SA Technologies Inc. <\/span><\/span>
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We’re Hiring: Staff Machine Learning Engineer <\/b><\/span><\/span><\/div>

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At SA Technologies Inc., we believe in turning career aspirations into reality. As a CMMI Level 5 and Great Place to Work® Certified global IT consulting and services company—and recognized as one of the Best Places for Women—we are committed to building an inclusive, supportive, and high -performance workplace <\/span><\/span>
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Job Description <\/span><\/span><\/span>
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Job Title: Staff Machine Learning Engineer
<\/span><\/span><\/span><\/b><\/span> Location: - San Jose, CA
<\/span><\/span><\/span><\/b><\/span> Full Time role
<\/span><\/span><\/span><\/b><\/span> Direct Client: <\/span><\/span><\/span><\/b><\/span><\/div>

100% Onsite role
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Job Description <\/span><\/b>
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This is a "full -stack" ML systems role for a senior individual
contributor and technical architect. You will be responsible for designing the
complete ML ecosystem for our edge devices, from the cloud -native MLOps
platform down to the bare -metal model optimization. <\/span>
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This unique role blends three key domains: <\/span>
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1. MLOps & Data: You will architect the
   entire data lifecycle, including our CI/CD pipelines, data -labeling loops,
   and on -device monitoring. <\/span>
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   1. Agentic & Edge AI: You will lead the
      design of autonomous agents that run on our edge devices, using domain
      knowledge in log analysis and computer vision. <\/span>
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      1. Systems & Hardware: You will be the
         "hardware -aware" expert, bridging our ML software with our
         silicon team to ensure our models are hyper -optimized for our
         custom NPU. <\/span>
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         You are the engineer who will not only build our ML platform but also
         design the intelligent agents it deploys and ensure they run faster and more
         securely than anyone else's. <\/span>
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         Key Responsibilities <\/span><\/u><\/b>
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         Architecture & Leadership: <\/span>
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         • Act as a senior individual contributor,
           leading by example with hands -on coding, design, and analysis across the
           entire ML stack. <\/span>
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           • Define the end -to -end architecture for our
             MLOps, agentic AI, and model optimization strategy. <\/span>
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             MLOps & Data Platform: <\/span>
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             • Design and implement our data processing and
               versioning pipelines, ensuring data integrity and traceability. <\/span>
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               • Build the infrastructure for
                 our Human -in -the -Loop (HITL) and AI -in -the -Loop (Active Learning) data
                 labeling systems to continuously improve our datasets. <\/span>
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                 • Develop a comprehensive, lightweight on -device
                   monitoring system to track not just operational metrics but also inference
                   quality and concept drift. <\/span>
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                   Agentic & Edge Development: <\/span>
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                   • Design and development of autonomous
                     agents that operate on our resource -constrained edge devices. <\/span>
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                     • Integrate deep domain knowledge, including
                       real -time log analysis, computer vision, and interaction with open -source
                       system tools. <\/span>
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                       Security & Optimization: <\/span>
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                       • Define and implement the complete security and
                         verification framework for our edge models. This includes MCP/A2A -like
                         secure protocols, MCP authentication, entity verification (e.g., model
                         signing), and model injection prevention. <\/span>
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                         • Serve as the primary technical bridge to our
                           silicon teams. Collaborate with RTL designers to influence
                           future NPU and FPGA architecture from an ML software perspective. <\/span>
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                           • Lead R&D on model optimization for our
                             specific AI inference engine, applying both graph -level (e.g., operator
                             fusion) and OP -level (e.g., custom ops) techniques. <\/span>
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                             Qualifications <\/span><\/b>
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                             • 8 -10+ years of hands -on experience in machine
                               learning, with a proven track record as a senior or staff -level individual
                               contributor. <\/span>
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                               • Ph.D. or M.S. in Computer Science, Electrical
                                 Engineering, or a related field (or equivalent practical
                                 experience). <\/span>
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                                 • Expert -level programming in Python and deep
                                   experience with ML frameworks (e.g., PyTorch, TensorFlow). <\/span>
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                                   • Deep theoretical understanding of modern ML
                                     algorithms (e.g., Transformers). <\/span>
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                                     • A strong foundational understanding of
                                       computer architecture, digital logic, and the role of RTL
                                       (Verilog/VHDL) in the hardware design lifecycle. <\/span>
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                                       • Proven experience architecting and building
                                         end -to -end MLOps lifecycles, from data ingestion to production monitoring
                                         and labeling loops. <\/span>
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                                         • Proven experience developing agentic
                                           systems or applications using LLMs. <\/span>
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                                           • Demonstrable domain knowledge in log
                                             analysis AND/OR computer vision. <\/span>
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                                             • Experience with on -device model
                                               security (verification, anti -injection) and secure communication
                                               protocols. <\/span>
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                                               • Hands -on experience optimizing models for
                                                 hardware (NPUs, GPUs) at graph and operator levels. <\/span>
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                                                 Why SA Technologies Inc.?
                                                 <\/b><\/b>
                                                 <\/b> Empowering Work Environment: A Great Place to Work, especially celebrated as one of the Best Places for Women. <\/b>
                                                 <\/b> Excellence and Quality: A CMMI Level 5 Company, ensuring operational and service excellence. <\/b>
                                                 <\/b> Globally Acclaimed: A Microsoft Gold Partner and Google Partner, with over 20 years of global IT consulting and Development solutions delivery. <\/b>

                                                 Have queries? We’re here to assist you!  Chat live <\/a> with our recruiter or connect with the job owner directly:
                                                 Email: View email address on jobs.jobcopilot.com <\/span><\/a><\/b><\/span><\/span><\/div>

                                                 
                                                 Embark on a rewarding journey together with us! At SA Technologies Inc., your journey begins with a friendly technical assessment, providing a stage to highlight your unique skills. <\/span><\/span><\/span><\/span><\/span><\/span><\/p>

                                                 
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