ml infrastructure engineer

Tymex

<div><p><b>Role Overview</b></p><p>
We are seeking a <b>Senior/Lead Platform Engineer</b> who will take ownership of the design, implementation and operation of our core data, analytics and ML infrastructure. This role spans across <b>platform architecture, DevSecOps, DataOps, and ML infrastructure</b>, and requires a combination of strategic thought leadership and hands-on execution. You will build, integrate and operate platforms on <b>AWS and Databricks</b>, enabling scalable, secure, production-grade ML/AI solutions.</p><p><b>
Key Responsibilities</b></p><ul><li>
Architect and implement end-to-end data and ML platforms: data lakes, warehouses, streaming and batch pipelines, model training/deployment infrastructure, on AWS + Databricks.</li><li>
Lead DevSecOps and DataOps practices: infrastructure as code (IaC), CI/CD pipelines for data &amp; ML workflows, secure multi-account/multi-region cloud operations.</li><li>
Integrate AWS services (e.g., S3, Redshift, Kinesis, Lambda, EKS/ECS) with Databricks runtime, Delta Lake, Unity Catalog etc to build scalable, performant pipelines.</li><li>
Build and operate ML infrastructure: training clusters, model versioning, MLOps toolchain (e.g., MLflow), model monitoring and observability, automatic retraining workflows.</li><li>
Establish data governance, lineage, quality, observability standards across data pipelines and ML workflows.</li><li>
Mentor engineering teams, define architectural best practices and guide implementation of high-scale data/ML systems.</li><li>
Optimize system performance, cost and scalability; diagnose and resolve large-scale production issues.</li><li>
Continuously evaluate new tools and technologies in the areas of cloud, data platform, DevSecOps, ML infrastructure and apply them to drive innovation.</li></ul><p><b>
Requirements</b></p><ul><li>
7+ years of experience in data platform architecture, cloud/ML infrastructure engineering or related roles.</li><li>
Deep technical expertise in <b>Databricks and AWS</b>: demonstrated ability to design, integrate and operate solutions spanning both platforms.</li><li>
Strong hands-on implementation skills: you will not just design but build, deploy and operate the platform.</li><li>
Proven track record of building and operating scalable ML/AI platforms in production (model training &amp; deployment).</li><li>
Expertise in Apache Spark, Delta Lake, modern data pipeline frameworks (batch + streaming).</li><li>
Strong background in infrastructure as code (Terraform, CloudFormation), CI/CD for data/ML, and DevSecOps practices.</li><li>
Proficiency in Python and SQL; familiarity with Scala or equivalent is a plus.</li><li>
Experience with data governance, data lineage, observability and MLOps frameworks (e.g., MLflow, Airflow, dbt).</li><li>
Bonus: Experience in fintech, regulated industries or high-security environments.</li></ul><p><b>
Benefits</b></p><ul>
<li>Performance bonus up to 2 months</li>
<li>13th month salary pro-rata</li>
<li>15-day annual leave+ 3-day sick leave + 1 birthday leave + 1 Christmas leave</li>
<li>Meal and parking allowance are covered by the company.</li>
<li>Full benefits and salary rank during probation.</li>
<li>Insurances as Vietnamese labor law and premium health care for you and your family without seniority compulsory</li>
<li>SMART goals and clear career opportunities (technical seminar, conference, and career talk) - we focus on your development.</li>
<li>Values-driven, international working environment, and agile culture.</li>
<li>Overseas travel opportunities for training and working related.</li>
<li>Internal Hackathons and company's events (team building, coffee run, blue card...)</li>
<li>Work-life balance 40-hr per week from Mon to Fri.</li></ul></div>

Senior/ Lead Platform Engineer (Databrick)

Keysight Technologies

<div>Overview:
<div>
Keysight accelerates innovation to connect and secure the world. Our solutions span wireless communications, semiconductors, aerospace/defense, automotive, and beyond. We combine measurement science, simulation, and advanced AI to help engineers design, simulate, and validate the world&rsquo;s most advanced systems. The Keysight AI Labs is pioneering scientific machine learning and physics &amp; T&amp;M-informed AI to transform Keysight&rsquo;s software, simulation, and measurement products.</div><div><br>
We are seeking a highly experienced and technically versatile Senior Data Engineer to join our AI infrastructure team. This role is critical to enabling scalable, secure, and high-performance data pipelines that support machine learning workflows. You will work closely with MLOps engineers, data scientists, and software developers to design and implement robust data systems that power model training, evaluation, and deployment at scale.</div>
Responsibilities:
<div><b>
Key Responsibilities</b></div><ul><li>
Architect and maintain end to end data pipelines for structured and unstructured data using tools like Spark, Airflow, and LakeFS.</li></ul><ul><li>
Design and implement data versioning, lineage, and governance strategies to support reproducibility , reliability and compliance.</li><li>
Collaborate with MLOps and ML engineering teams to integrate data workflows into model training and deployment pipelines.</li><li>
Optimize data storage layers and retrieval across hybrid environments (on-prem and AWS), ensuring performance and cost-efficiency.</li><li>
Develop APIs and SDKs to enable self-service data access for internal ML teams.</li><li>
Lead data infrastructure design reviews and mentor junior engineers on best practices.</li><li>
Contribute to the development of internal tools for data curation, labeling, and augmentation.</li></ul>
Qualifications:
<div><b>
Required Qualifications</b></div><ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Engineering, or related field.</li><li>
7+ years of experience in data engineering, with a strong focus on ML/AI infrastructure.</li><li>
Proficiency in Python, SQL, and distributed data processing frameworks (e.g., Spark, Dask).</li><li>
Experience with data orchestration tools (e.g., Airflow, Prefect) and version control systems (e.g., LakeFS, DVC).</li><li>
Deep understanding of data modeling, ETL/ELT pipelines, and data quality frameworks.</li><li>
Proficient with cloud platforms (AWS preferred) and containerized environments (Docker, Kubernetes).</li></ul><div><b>
Preferred Qualifications</b></div><ul><li>
Experience supporting MLOps workflows and integrating with ML platforms (e.g., MLflow, Kubeflow).</li><li>
Knowledge of data privacy, security, and compliance in regulated environments.</li><li>
Strong communication skills and ability to work cross-functionally in a fast-paced R&amp;D environment.</li><li>
Advanced statistical and analytics background to provide transformation checks, quality checks, informative data profiling, etc.</li></ul><div></div><div><br>
Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***</div></div>

Data Engineer, Expert

Clariti Cloud Inc.

<p></p><div><div><p>Join our mission to provide governments with exceptional experiences so they can do the same for their communities!</p>
<h1 class="jobSectionHeader"><b>
What do we do?</b></h1>
<p><b>
We empower governments to deliver exceptional citizen experiences.</b></p>
<p>
Check out our <b>'About Us'</b><b> </b>page for a deep dive into our product and what makes us exceptional.</p></div><p><b>
How will you help us make an impact? &zwj;&zwj;</b></p>
<p>
The <b>Senior MLOps Engineer</b> will design, build, and scale the systems that power CivCheck and Clariti's AI capabilities. As the first MLOps Engineer, you will lead the development of robust ML infrastructure, ensuring that models move efficiently from research to production with reliability, observability, and performance at scale.This role is ideal for someone who thrives at the intersection of machine learning, software engineering, and cloud infrastructure, and who's motivated to enable teams to deliver high-impact ML systems efficiently and safely.</p>
<p><b>
As a X at Clariti, you'll get to :</b></p>
<ul>
<li>Design and maintain end-to-end ML pipelines for training, evaluation, and deployment of models and agentic AI workflows</li>
<li>Build and optimize infrastructure for distributed training and model serving across GPU and cloud environments.</li>
<li>Develop tools for data creation, model versioning, experiment &amp; performance tracking, and automated retraining.</li>
<li>Collaborate with AI researchers and ML engineers to productionize POCs and ensure model reproducibility and scalability.</li>
<li>Implement CI/CD best practices for ML systems, including continuous integration, automated testing, and deployment workflows.</li>
<li>Monitor and manage model health, performance, drift, and data quality in production.</li>
<li>Partner with Engineering teams to streamline infrastructure provisioning and data access.</li>
<li>Drive cost optimization and performance tuning for large-scale model training.</li>
<li>Contribute to internal documentation and best practices.</li>
</ul>
<p><b>What do you bring to the team?</b></p>
<ul>
<li>6&ndash;10+ years of experience in software or ML engineering, with at least 3+ in MLOps or ML infrastructure.</li>
<li>Solid experience working with Python, C, C++, Bash, etc.</li>
<li>Proven experience deploying and managing ML models in production.</li>
<li>Proficiency with Docker, and Kubernetes for scalable ML system design.</li>
<li>Experience with cloud platforms (AWS, GCP, or Azure) and GPU orchestration.</li>
<li>Hands-on knowledge of CI/CD pipelines (GitHub Actions, Jenkins, or similar).<br>
Familiarity with MLflow, Weights &amp; Biases, Kubeflow, and other similar tools for experiment tracking and pipeline automation.</li>
<li>Solid understanding of data versioning, model reproducibility, and monitoring strategies.</li>
<li>Excellent problem-solving skills and a collaborative, team-oriented mindset.</li>
</ul>
<p><b>Bonus Points</b></p>
<ul>
<li>Experience training models from scratch, including defining architectures, curating &amp; cleaning datasets, tuning training parameters, and bringing models from research to monitored production.</li>
<li>Exposure to model optimization techniques (quantization, distillation, TensorRT, ONNX).</li>
<li>Familiarity with infrastructure-as-code tools (Terraform, CloudFormation).</li>
<li>Background in distributed systems or high-performance computing.</li>
<li>Contributions to open-source projects</li>
</ul>
<p><b>What's in it for you?</b></p>
<p><b>
We invest in and empower our team members with competitive compensation packages, well deserved time off and benefits to keep you and your family healthy! *</b></p>
<p>
 The base salary range for this role is expected to be between <b>$190,000-240,000 </b>based on the candidate's skills, experience, and qualifications while considering internal pay equity and our broader pay philosophy.</p>
<p>
If you have questions about compensation as we move through the process, we're happy to discuss further.</p>
<ul><li><i>Benefits depend on employment type (full-time, part-time, contract, etc).</i></li></ul><p></p><div><h1 class="jobSectionHeader"><b><br>
Things to Note</b></h1>
<p><b>
Background checks</b> - Because our customers trust us with sensitive information, we require all successful candidates to undergo comprehensive background checks before joining our team. We focus strictly on global sanctions and criminal offences that are directly relevant to employment at Clariti, and follow all applicable privacy and human rights legislation.</p>
<p><b>
Travel</b>- Although we operate as a remote company, all roles are expected to participate in occasional travel for in-person company-wide or departmental meetings, typically 1-2 times per year. Additional travel requirements specific to the role, if any, will be outlined in the job description.</p>
<p>
We're committed to building an inclusive culture where our team members <b>take ownership</b> over projects, tasks, and outcomes; bring a <b>growth mindset</b> to drive continuous learning and self-development; have the ability to <b>communicate courageously</b> in a direct but respectful way; and are <b>customer-focused</b> by keeping the customer at the heart of decision-making. It's the diversity of our team that helps us make better decisions, by leveraging the diversity in thought &amp; experience across to create impactful solutions as we explore new paths &amp; challenges as we grow. We're working to create a workplace and team that is as diverse as the communities we serve. <b>We welcome and encourage candidates of all backgrounds to apply.</b></p>
<h1 class="jobSectionHeader"><b>
Questions? We are here to help</b></h1>
<p>
If you require accommodations in completing an application, interviewing, completing any pre-employment testing, or otherwise participating in our hiring process for any reason, please direct your questions to hr@claritisoftware.com and we'll be happy to support you.</p></div></div>

Senior MLOps Engineer

Google

<div><h3 class="jobSectionHeader"><b>Minimum qualifications:</b></h3><ul>
<li>Bachelor&rsquo;s degree or equivalent practical experience.<br>
</li>
<li>8 years of experience in software development.<br>
</li>
<li>7 years of experience leading technical project strategy, ML design, and working with industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).</li>
<li>5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.<br>
</li>
<li>5 years of experience with design and architecture, and testing/launching software products.</li></ul><br>
<h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul>
<li>Experience with Machine Learning, Distributed Computing, Build Infrastructure, and Cluster Management.</li>
<li>Experience with C++, Python, Machine Learning Infrastructure, Compilers, Computer Architecture, Debugging, etc.</li>
<li>Experience in a technical leadership role, with the ability to lead complex, cross-functional engineering projects from conception to completion.</li>
</ul><div><h2 class="jobSectionHeader"><b>About the job</b></h2><p>
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google&rsquo;s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.</p>
<p>
The Machine Learning (ML) Strategy and Allocation Committee (MLSA) Technical Core Team is a central technical body responsible for shaping the future of Google's AI by optimizing the vast ML compute resources. As Google's investment in AI accelerates, the efficient allocation, strategic alignment, and technical governance of the ML fleet are paramount to the success.
</p><p>In this role, you will develop the frameworks, policies, and technical strategies that ensure the ML compute capacity is aligned with Google's strategic priorities, used with maximum efficiency, and operates as a consistent, exceptional system. Your work spans the entire ML domain, taking on complex challenges in infrastructure efficiency, technical governance, and resource allocation at a scale that is unprecedented in the industry.</p><p>
The AI and Infrastructure team is redefining what&rsquo;s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
</p><p>We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.</p><p>
The US base salary range for this full-time position is $248,000-$349,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.</p></div><div><h2 class="jobSectionHeader"><b>
Responsibilities</b></h2><ul>
<li>Lead technical analysis across Google&rsquo;s ML infrastructure (including training, serving, and scheduling) to identify opportunities for efficiency gains, cost optimization, and improved resource utilization. Develop data-driven proposals and recommendations for executive leadership.</li>
<li>Partner with executive technical leads across serving, training, scheduling, and fleet management to establish and drive technical governance.</li>
<li>Collaborate with MLSA leadership to translate Google's strategic AI priorities into a concrete technical roadmap for the ML compute resources, ensuring the capacity planning and allocation strategies support critical initiatives.</li>
<li>Serve as a key technical consultant and guide for Product Areas (PAs) and engineering organizations. Help them navigate MLSA policies, optimize their capacity consumption, and align their roadmaps with Google&rsquo;s overall ML strategy.</li>
<li>Develop and advocate technical proposals for new frameworks, tools, and systems that enable more efficient and dynamic allocation of ML resources.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Senior Staff Software Engineer, GenAI, Performance Engineering

<div><h3 class="jobSectionHeader"><b>Minimum qualifications:</b></h3><ul>
<li>Bachelor's degree or equivalent practical experience.</li>
<li>8 years of experience in software development.</li>
<li>7 years of experience leading technical project strategy, ML design, and working with industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).</li>
<li>5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.</li>
<li>5 years of experience with design and architecture and testing or launching software products.</li></ul><br>
<h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul>
<li>Experience in leading and delivering ML projects focused on on-device deployment (Android, iOS, web browsers, or embedded devices).</li>
<li>Experience in ML frameworks, e.g., PyTorch, JAX, TensorFlow.</li>
<li>Experience with on-device ML SDKs/tooling, (e.g., TensorFlow Lite, ExecuTorch, Core ML, SNPE/QNN).</li>
<li>Knowledge of ML converters/compilers and run times, and hardware-accelerated ML inference techniques.</li>
<li>Understanding of Generative AI model architectures and their optimization for on-device execution.</li>
<li>Passion for innovation and to advance what's possible with on-device ML.</li>
</ul><div><h2 class="jobSectionHeader"><b>About the job</b></h2><p>
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google&rsquo;s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.</p>
<p>
The AI and Infrastructure team is redefining what&rsquo;s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
</p><p>We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.</p><p>
The US base salary range for this full-time position is $248,000-$349,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.</p></div><div><h2 class="jobSectionHeader"><b><br>
Responsibilities</b></h2><ul>
<li>Develop and guide critical projects in Google's on-device ML infrastructure.</li>
<li>Enable on-device deployment of key models, across various accelerators (GPU/Pixel TPU/NPUs/CPU) on Android, Chrome, and more.</li>
<li>Improve performance of on-device model inference via optimizations in the model structure, on-device runtime and kernel implementation.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Senior Staff Software Engineer, On-Device Machine Learning

General Motors

<div><p><b>Job Description
</b></p><div><div><p>Principal AI/ML Engineer, AV ML Infra
</p></div><div><p>We&rsquo;re General Motors (GM), a company driving the future of mobility with advanced self-driving and electric vehicle technologies.
</p></div><div><p>We&rsquo;re building the world&rsquo;s most innovative autonomous vehicles to safely connect people to the places, things, and experiences they care about. We believe self-driving vehicles will help save lives, reshape cities, give back time in transit, and restore freedom of movement for many.
</p></div><div><p>GM employees have the opportunity to grow and develop while learning from leaders at the forefront of their fields. With a culture of internal mobility, there&rsquo;s an opportunity to thrive in a variety of disciplines. This is a place for dreamers and doers to succeed.
</p></div><div><p>If you are looking to play a part in making a positive impact in the world by advancing the revolutionary work of self-driving vehicles, join us.
</p></div><div><p><b>About the team:
</b></p></div><div><p>The AV ML Infra team at GM builds ML infrastructure designed to meet the unique demands of AI and ML innovation, supporting a wide range of use cases across teams such as Embodied AI, Simulation, Data Science, and more. We enable scalable and efficient ML experimentation, enhance the productivity of ML engineers, and drive the adoption of cutting-edge ML techniques.
</p></div><div><p>Our ML infrastructure includes:
</p></div><div><ul><li><p><b>AI Validation &amp; Inference: </b>Ensures robust model performance by running large-scale simulation workloads and managing reliable ML inference pipelines.<br>
<br>
</p></li></ul></div><div><ul><li><p><b>ML Compute: </b>Streamlines and optimizes large-scale ML training and inference across cloud and on-prem compute resources.<br>
<br>
</p></li></ul></div><div><ul><li><p><b>AV Pipelines &amp; Lineage: </b>Automates ML workflows while tracking data and model lineage across diverse infrastructures, accelerating engineering velocity and ensuring reproducibility.
</p></li></ul></div><div><p>Together, these tools and systems empower GM to tackle the complexities of autonomous driving technology and expedite our path to commercialization.
</p></div><div><p><b>Position Overview:
</b></p></div><div><p>The Principal AI/ML Engineer will lead a growing organization, guiding the AV ML Infra team in achieving its mission while shaping a long -term vision and execution strategies across GM&rsquo;s AI and ML efforts. This leadership role will drive a transformative leap in our infrastructure capabilities to meet the scale we anticipate . The leader will articulate a clear vision and strategy, design an organizational structure to enable effective execution, and cultivate strong partnerships across cross-functional teams and stakeholders.
</p></div><div><p><i>Note: This role is part of an ML infrastructure engineering team and does not involve applying machine learning models for specific tasks. The focus is on developing infrastructure products that empower GM teams to perform machine learning and data science at </i><i>scale </i><i>.
</i></p></div><div><p><b>What </b><b>you&rsquo;ll </b><b>be doing:
</b></p></div><div><ul><li><p><b>Design &amp; Implementation: </b>Utilize the latest cloud technologies (GCP/Azure) to design, implement, and test scalable distributed computing and data processing solutions in the cloud.
</p></li></ul></div><div><ul><li><p><b>Project Ownership: </b>Take ownership of technical projects from inception to completion, contribute to the product roadmap, and make informed decisions on major technical trade-offs.
</p></li></ul></div><div><ul><li><p><b>Collaboration: </b>Engage effectively in team planning, code reviews, and design discussions, considering the impact of projects across multiple teams while proactively managing conflicts.
</p></li></ul></div><div><ul><li><p><b>Mentorship &amp; Recruitment: </b>Conduct technical interviews with calibrated standards, onboard, and mentor engineers and interns, fostering a culture of growth and knowledge sharing.
</p></li></ul></div></div><div><div><p><b>What you must have:
</b></p></div><div><ul><li><p>10+ years of experience, with a strong background in large-scale distributed systems preferred.
</p></li></ul></div><div><ul><li><p>5+ years of experience leading and driving large-scale initiatives.
</p></li></ul></div><div><ul><li><p>Proficiency in building scalable infrastructure on the cloud using Python, C++, Golang, or similar languages.
</p></li></ul></div><div><ul><li><p>Experience working with relational and NoSQL databases.
</p></li></ul></div><div><ul><li><p>Demonstrated ability to develop and maintain systems at scale.
</p></li></ul></div><div><ul><li><p>A Bachelor&rsquo;s, Master&rsquo;s, or Ph.D. in Computer Science, Electrical Engineering, Mathematics, Physics, or a related field; or equivalent practical experience.
</p></li></ul></div><div><ul><li><p>A passion for autonomous vehicle technology and its transformative potential.
</p></li></ul></div><div><ul><li><p>Strong attention to detail and a commitment to accuracy.
</p></li></ul></div><div><ul><li><p>A proven track record of efficiently solving complex problems.
</p></li></ul></div><div><ul><li><p>A startup mentality with a willingness to embrace uncertainty and wear multiple hats.
</p></li></ul></div><div><p><b>Bonus Points:
</b></p></div><div><ul><li><p>Experience with Google Cloud Platform, Microsoft Azure, or Amazon Web Services.
</p></li></ul></div><div><ul><li><p>Experience with open-source orchestration platforms such as Kubeflow, Flyte, Airflow, etc.
</p></li></ul></div><div><ul><li><p>Experience with Kubernetes.
</p></li></ul></div><div><ul><li><p>Understanding of Machine Learning (ML) models/pipelines.
</p></li></ul></div><div><ul><li><p>Python/C++/Golang proficiency .
</p></li></ul></div><div><ul><li><p>Relevant publications.<br>
<br>
<br>
</p></li></ul></div></div><p></p>&amp;#xa;&amp;#xa;&amp;#xa;&amp;#xa;
<p><b>About GM
</b></p><p>Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.
</p><p></p><p><b>Why Join Us
</b></p><p>We believe we all must make a choice every day &ndash; individually and collectively &ndash; to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.
</p><p></p><p><b>Benefits Overview
</b></p><p>From day one, we're looking out for your well-being&ndash;at work and at home&ndash;so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting <b>Total Rewards resources </b>.
</p><p></p><p><b>Non-Discrimination and Equal Employment Opportunities (U.S.)
</b></p><p>General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.
</p><p></p><p>All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.
</p><p></p><p>We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit <b>How we Hire </b>.
</p><p></p><p><b>Accommodations
</b></p><p>General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, <b>email </b>us or call us at 800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.</p></div><p></p>

Principal Staff AI/ML Engineer

<div><h3 class="jobSectionHeader"><b>Minimum qualifications:</b></h3><ul>
<li>Bachelor&rsquo;s degree or equivalent practical experience.<br>
</li>
<li>2 years of experience with software development or 1 year of experience with an advanced degree in an industry setting.</li>
<li>1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging).</li></ul><br>
<h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul>
<li>Master's degree or PhD in Computer Science or related technical fields.<br>
</li>
<li>2 years of experience with data structures or algorithms.</li>
<li>Experiences in machine learning infrastructures such as data/model serving and training and model tuning experience.</li>
<li>Experience developing accessible technologies.<br>
</li>
</ul><div><h2 class="jobSectionHeader"><b>About the job</b></h2><p>
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google&rsquo;s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.</p>
<p>
Google Play offers music, movies, books, apps and games for devices, powered by the cloud. It syncs across devices and on the web. As part of the Android and Mobile team, Googlers working on Google Play do everything from engineering our backend systems, to shaping product strategy, to forming great content partnerships. They make it possible for people to do things like buy an ebook or song on their Android phone, then have it instantly available on their laptop. The Google Play team enhances the Android ecosystem by giving developers and partners a premium store where they can reach millions of users.</p><p>
The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.</p></div><div><h2 class="jobSectionHeader"><b>
Responsibilities</b></h2><ul>
<li>Develop ML data Solutions for feature engineering and training data generation including indexing/storage/serving solutions.</li>
<li>Empower model deployment infrastructure and training infrastructure on large-scale TPU clusters.</li>
<li>Advance Play ML infrastructure to support the next wave of recommendation experiences with reliability and efficiency at its core.</li>
<li>Design and develop AI models (e.g., Transformers models) using Google Play data, scaling across billions of users and millions of apps.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Software Engineer, Play Recommendation and ML Infrastructure

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