ai infrastructure engineer

Millennium Management

<div>AI Platform Engineer
We&rsquo;re seeking an AI Platform Engineer to contribute to the development and management of cutting-edge AI infrastructure for our complex enterprise environment. In this role, you&rsquo;ll harness your expertise to build infrastructure which enables your team and the firm to manage autonomous agents, machine learning systems and other applications in the AI domain.
You&rsquo;ll design and manage federated AI ecosystems, including MCP servers, agents and enterprise AI tooling, while orchestrating agent deployment across distributed systems and service buses. This role requires technical depth, strong communication, and a passion for building transformative AI infrastructure.
If you&rsquo;re ready to shape the future of AI and thrive in a fast-paced, innovative environment, we want to hear from you!
Key Responsibilities:<ul><li>
Design and implement AI infrastructure to support federated agent development and distributed deployment across the organization.</li><li>
Manage and orchestrate AI agents to generate architecturally sound code, ensuring adherence to enterprise standards and best practices.</li><li>
Build and maintain MCP (Model Context Protocol) servers and related infrastructure for agent communication, coordination, and enterprise service bus integration.</li><li>
Accelerate code review processes by leveraging AI agents for automated analysis, quality checks, and architectural validation.</li><li>
Establish robust monitoring, governance, and security frameworks for AI agent operations in enterprise environments.</li><li>
Implement and manage secure authentication and authorization systems for MCP servers, including OAuth flows and API security.</li><li>
Collaborate with development teams to integrate AI-powered tools into existing workflows and CI/CD pipelines.</li><li>
Act as a deployed engineer, traveling to different teams across the firm to teach AI infrastructure best practices and guide adoption.</li><li>
Provide technical leadership in transitioning traditional development practices to AI-augmented approaches.</li></ul>
Qualifications:<ul><li>
Experience: 8+ years of professional software development experience with a demonstrated ability to architect and build scalable systems.</li><li>
AI Infrastructure: Experience with AI/ML infrastructure, agent orchestration, or similar AI-powered development tools.</li><li>
Programming Skills: Proficiency in Python, TypeScript/JavaScript, and experience with AI/ML frameworks and libraries.</li><li>
Enterprise Architecture: Strong understanding of enterprise software architecture patterns and distributed systems design.</li><li>
Cloud Platforms: Experience with cloud platforms (AWS, Azure, or GCP) and infrastructure-as-code tools.</li><li>
Containerization: Experience with Docker, Kubernetes, and container orchestration in production environments.</li><li>
API Design: Experience building and managing APIs, microservices, and event-driven architectures.</li><li>
Security: Strong understanding of information security principles, OAuth 2.0/OpenID Connect flows, API security, and secure system design.</li><li>
Communication: Strong communication and teaching skills with the ability to work as a deployed engineer across different teams.</li><li>
Education: Bachelor's or Master's degree in Computer Science, Engineering, or related technical field.</li></ul>
Preferred Qualifications:<ul><li>
Experience with AI agent frameworks, LLM integration, or Model Context Protocol (MCP) implementations.</li><li>
Background in building federated systems or multi-tenant AI platforms.</li><li>
Experience with AI governance, security, and compliance in enterprise environments.</li><li>
Background in information security, penetration testing, or security architecture roles.</li><li>
Familiarity with code generation tools, automated testing frameworks, and AI-powered development workflows.</li><li>
Knowledge of vector databases, embedding systems, and retrieval-augmented generation (RAG) architectures.</li><li>
Experience in DevOps/Platform Engineering roles with focus on developer tooling and productivity.</li><li>
Previous experience managing transitions from traditional to AI-augmented development practices.</li></ul>
The estimated base salary range for this position is $175,000 to $250,000, which is specific to New York and may change in the future. Millennium pays a total compensation package which includes a base salary, discretionary performance bonus, and a comprehensive benefits package. When finalizing an offer, we take into consideration an individual&rsquo;s experience level and the qualifications they bring to the role to formulate a competitive total compensation package.</div>

AI Platform Engineer

Movius Interactive

<div><h1 class="jobSectionHeader">Job Title: ML Ops Engineer &ndash; Speech AI &amp; Infrastructure (5&ndash;8 Years)</h1>
<h2 class="jobSectionHeader">Location: Bangalore (India)</h2>
<h2 class="jobSectionHeader">Full-Time | Immediate Joiners Preferred</h2>
<h3 class="jobSectionHeader">Role Summary:</h3>
We are looking for an experienced ML Ops Engineer (5&ndash;8 years) with a strong background in operationalizing AI/ML systems, particularly in speech AI agents integrated into telephony environments. This role bridges AI infrastructure, voice bot deployment, and real-time streaming operations, enabling AI models to function reliably in production use cases such as customer collections, voice-based load bookings, and conversational AI in logistics and telecom.
<h3 class="jobSectionHeader">Key Responsibilities:</h3>
<ul><li>Build, deploy, and maintain real-time speech AI agents for telephony (inbound/outbound) using CPaaS platforms and audio pipelines.</li>
<li>Integrate ASR (Automatic Speech Recognition), TTS (Text-to-Speech), and LLMs with voice bot workflows using WebSocket or RTP streams.</li>
<li>Work closely with backend engineers and AI scientists to deploy scalable ML models into production across Kubernetes, Docker, and cloud-native environments (AWS/GCP).</li>
<li>Set up observability, logging, and monitoring of speech pipelines (latency, dropouts, stream integrity) using Prometheus, Grafana, ELK, etc.</li>
<li>Automate the ML lifecycle and CI/CD for AI models using tools like MLflow, Airflow, or Kubeflow.</li>
<li>Manage streaming latency optimization across ASR, LLM, and TTS chains in low-latency applications like telephony bots.</li>
<li>Ensure fault-tolerant, secure, and compliant deployment of voice-based systems using industry-standard DevOps practices.</li>
</ul><h3 class="jobSectionHeader">Required Skills:</h3>
<ul><li>5&ndash;8 years of experience in ML Ops, AI platform engineering, or DevOps with hands-on ML deployment.</li>
<li>Experience with ASR/TTS model integration (e.g., Whisper, Amazon Polly, Google Speech API).</li>
<li>Hands-on experience deploying AI in telephony environments, with working knowledge of Asterisk, FreeSWITCH, or similar systems.</li>
<li>Solid command over WebSocket, SIP, RTP, or similar streaming protocols for voice integration.</li>
<li>Proficient with cloud services (AWS/GCP/Azure), containers (Docker), orchestration (Kubernetes), and infrastructure as code (Terraform).</li>
<li>Experience with end-to-end CI/CD pipelines, GitOps, and model monitoring (accuracy, drift, performance).</li>
<li>Strong programming in Python and scripting to support infrastructure and integration tasks.</li>
</ul><h3 class="jobSectionHeader">Nice to Have:</h3>
<ul><li>Exposure to CPaaS platforms (e.g., Twilio, Vonage, Kaleyra, Exotel) for voice bot integration.</li>
<li>Familiarity with conversational AI/NLU platforms and agentic AI frameworks.</li>
<li>Prior experience supporting AI agents in collections, logistics/freight, or telecom workflows.</li>
</ul><h3 class="jobSectionHeader">What We Offer:</h3>
<ul><li>Work on next-gen AI voice agents deployed in high-impact customer environments.</li>
<li>Influence platform architecture and deliver cutting-edge infrastructure for real-time ML.</li>
<li>High-ownership, engineering-led culture with strong product alignment and technical mentorship.</li></ul></div>

MLOPS ENGINEER

Think Big Solutions

About the Role: We&rsquo;re looking for an experienced engineer with hands-on expertise in building and deploying agentic systems and large-scale data pipelines. This is a high-impact founding opportunity for someone who thrives in fast-paced startup environments and wants to shape the technical direction from day one.You&rsquo;ll play a pivotal role in building the core AI infrastructure, collaborating directly with leadership to turn complex problems into scalable, production-ready systems.Responsibilities:<ul><li>Architect and deploy scalable backend systems and cloud infrastructure for AI-driven products.</li><li>Lead technical design and decision-making for new systems and tools.</li><li>Build reliable APIs and data pipelines supporting interoperability across healthcare systems.</li><li>Collaborate cross-functionally with leadership, engineering, and product teams.</li><li>Take full ownership from design to deployment and ongoing optimization.</li></ul>Requirements:<ul><li>5&ndash;15 years of professional software engineering experience.</li><li>Proven experience leading teams or acting as a founding/principal engineer in startup environments.</li><li>Strong background in JavaScript/TypeScript, Python, and Next.js.</li><li>Proficiency with AWS, Terraform, Docker, and CI/CD pipelines.</li><li>Familiarity with Postgres and scalable cloud architecture.</li><li>Understanding of HIPAA or regulated environments is an asset.</li><li>Degree from a top 50 U.S. university preferred.</li></ul>What&rsquo;s Offered:<ul><li>Competitive compensation package (base + equity)</li><li>Full health, dental, and vision coverage</li><li>Wellness and gym membership allowance</li><li>Option to live and collaborate in a 3,500 sq. ft. hackerhouse</li><li>Opportunity to work with cutting-edge AI technologies shaping the future of healthcare</li></ul>Job Type: Full-timePay: $120,000.00 - $250,000.00 per yearWork Location: In person

Founding DevOps Engineer

Guardian management services

Job Specification: AI Platform EngineerAbout the RoleWe are seeking an AI Platform Engineer to build and scale the infrastructure that powersour production AI services. You will take cutting-edge models&mdash;ranging from speechrecognition (ASR) to large language models (LLMs)&mdash;and deploy them into highlyavailable, developer-friendly APIs.You will be responsible for creating the bridge between the R&amp;D team, who train models,and the applications that consume them. This means developing robust APIs, deployingand optimizing models on Triton Inference Server (or similar frameworks), and ensuringreal-time, scalable inference.Responsibilities&#9679; API Development&#9675; Design, build, and maintain production-ready APIs for speech, language, andother AI models.&#9675; Provide SDKs and documentation to enable easy developer adoption.&#9679; Model Deployment&#9675; Deploy models (ASR, LLM, and others) using Triton Inference Server orsimilar systems.&#9675; Optimize inference pipelines for low-latency, high-throughput workloads.&#9679; Scalability &amp; Reliability&#9675; Architect infrastructure for handling large-scale, concurrent inferencerequests.&#9675; Implement monitoring, logging, and auto-scaling for deployed services.&#9679; Collaboration&#9675; Work with research teams to productionize new models.&#9675; Partner with application teams to deliver AI functionality seamlessly throughAPIs.&#9679; DevOps &amp; Infrastructure&#9675; Automate CI/CD pipelines for models and APIs.&#9675; Manage GPU-based infrastructure in cloud or hybrid environments.Requirements&#9679; Core Skills&#9675; Strong programming experience in Python (FastAPI, Flask) and/orGo/Node.js for API services.&#9675; Hands-on experience with model deployment using Triton Inference Server,TorchServe, or similar.&#9675; Familiarity with both ASR frameworks and LLM frameworks (HuggingFace Transformers, TensorRT-LLM, vLLM, etc.).&#9679; Infrastructure&#9675; Experience with Docker, Kubernetes, and managing GPU-acceleratedworkloads.&#9675; Deep knowledge of real-time inference systems (REST, gRPC, WebSockets,streaming).&#9675; Cloud experience (AWS, GCP, Azure).&#9679; Bonus&#9675; Experience with model optimization (quantization, distillation, TensorRT,ONNX).&#9675; Exposure to MLOps tools for deployment and monitoringJob Types: Full-time, PermanentPay: From &#8377;50,000.00 per monthExperience:<ul><li>total work: 3 years (Preferred)</li></ul>Work Location: In person

AI Platform Engineer -2- 4 years exp

careem

<div>
About the team: 
The AI Acceleration Office builds the intelligence layer that powers Careem s ecosystem, and we are looking for a Senior Software Engineer to drive architecture and development of it. Our mission is to drive competitive value through an Agentic AI Platform, a system that can design, orchestrate, and manage autonomous AI agents across customer and operational journeys. 
 About the role: 
As a Senior Software Engineer, you ll lead the architecture and development of the AI Agent Creation and Management Platform, an intelligent layer that enables scalable agent creation, orchestration, lifecycle management, and performance monitoring. You ll work acrossbackend systems, AI infrastructure, and data orchestration, designing abstractions that connect LLMs, context, memory, and state into real-time adaptive agents. This is a hands-on leadership role, you ll design systems, ship code, mentor engineers, and influence Careem s long-term AI platform strategy./p&gt;

What you ll do: 
<ul style="">
<li>
Architect and implement the foundational services for Careem s Agentic AI Platform, covering agent creation APIs, orchestration pipelines, state machines, and monitoring layers./p&gt;

</li>
<li>
Design abstractions for multi-agent collaboration, memory persistence, and reasoning cycles integrated./p&gt;

</li>
<li>
Build scalable orchestration frameworks (LangGraph, or custom) that coordinate model calls, context injection, and multi-turn workflows across internal and external agents./p&gt;

</li>
<li>
Develop observability and governance systems for AI agents: tracing, metrics, auditing, and self-healing./p&gt;

</li>
<li>
Integrate LLM-based and retrieval-augmented components into backend services with strict latency, reliability, and compliance requirements./p&gt;

</li>
<li>
Work with data scientists and ML engineers to operationalize models (embedding stores, vector databases, evaluation pipelines, model versioning)./p&gt;

</li>
<li>
Establish standards for agent safety, lifecycle management, and deployment reliability across Careem s product ecosystem./p&gt;

</li>
<li>
Mentor engineers and shape platform-wide engineering practices around AI integration and distributed systems design./p&gt;

</li>
</ul>
What you ll need: 
<ul style="">
<li style="">
6+ years of backend or distributed systems engineering experience, with 2 3 years in AI/ML infrastructure or LLM-based systems./p&gt;

</li>
<li style="">
Deep hands-on experience in Python and Go, with production experience in building scalable, event-driven architectures./p&gt;

</li>
<li style="">
Expertise in orchestration and distributed compute (Kubernetes)./p&gt;

</li>
<li style="">
Experience in building end-to-end event-drive architecture and data pipelines (Kafka, Airflow and Flink)/p&gt;

</li>
<li style="">
Familiarity with agentic frameworks (LangGraph, LangChain, AutoGen) and design of multi-agent or RAG systems./p&gt;

</li>
<li style="">
Experience in integrating LLMs and vector stores (FAISS, Pinecone, Weaviate, Milvus) into backend applications./p&gt;

</li>
<li style="">
Solid understanding of model and agent observability, monitoring, and continuous evaluation./p&gt;

</li>
<li style="">
Strong architectural skills, capable of designing systems that balance scalability, cost, and experimentation velocity./p&gt;

</li>
<li style="">
Experience working with data streaming, metrics, and real-time feedback loops./p&gt;

</li>
<li style="">
Growth mindset and bias for ownership, you thrive in high-autonomy, fast-paced, and purpose-driven environments./p&gt;

</li>
</ul>
</div>

Senior Software Engineer II - AI Platform

City and County of San Francisco

<div>Company Description 
Department: DT/Emergent Technology 
Job class: 1042 IS Engineer 
Salary range: [$138,684.00 - $174,434.00] annually 
Hours: Full-time. 
Role type: Permanent Exempt (PEX), Full Time position is excluded by the Charter from the competitive civil service examination process and shall serve at the discretion of the appointment officer. The anticipated duration of this project position is thirty-six (36) months and will not result in an eligible list or permanent civil service hiring. Project-based positions cannot be ongoing or exceed 36 months.
About:<ul><li>
Application Opening: Monday, November 10, 2025</li><li>
Application Deadline: This job will close no sooner than Monday, November 24, 2025 (11:59 PM).</li></ul>
Department Description:
Are you ready to make an impact in one of the most innovative cities? The Department of Technology (DT) is looking for passionate IT professionals to help shape the future of technology in San Francisco! As the centralized technology services provider for the City and County of San Francisco (CCSF), DT delivers critical infrastructure and services to over 33,000 employees&mdash;supporting public safety, municipal broadband, cybersecurity, cloud solutions, and more! With a $140M+ annual budget and a team of 300+ experts, DT is leading the charge in digital transformation. DT provides services through our core areas of IT Excellence:<ul><li>
IT Project Management Office</li><li>
Enterprise Application Services</li><li>
Cloud Center of Excellence</li><li>
IT Operations and Support including the Service Desk and NOC</li><li>
City Infrastructure including the Network, Telcom and Data Centers</li><li>
Office of Cybersecurity including Cyber Defense, Identity Management and Disaster Recovery</li><li>
Public Safety Systems and Municipal Broadband Fiber</li><li>
SFGovTV Broadcasting Services</li><li>
IT Finance and Administration Services</li><li>
Emerging Technologies</li></ul>
Why Join Us? Innovative &amp; Impactful Work At DT, you won&rsquo;t just work on IT&mdash;you&rsquo;ll power a city. Your expertise will directly impact the residents of San Francisco, from closing the digital divide to ensuring secure, efficient city operations.
Benefits of Working for CCSF: In addition to challenging and rewarding work, the City provides a generous suite of benefits to its employees.<ul><li>
Competitive pay, benefits, and retirement options</li><li>
Career growth opportunities through training, internal mobility, and subsidized education</li><li>
Diverse work environment in a diverse city</li><li>
We offer employees the ability to work from home one day a week while spending the other four days in our San Francisco office, promoting both collaboration and work-life balance</li></ul>
We are committed to ensuring that the City services are inclusive, efficient, equitable, and culturally competent for San Franciscans of all races, ethnic backgrounds, religions, and sextual orientations. This commitment requires comprehensive review and thorough analysis of existing practices and policies to remove barriers to real inclusion. We are also committed to ensuring that we have a safe, equitable, and inclusive workplace for individuals of all races. This includes creating opportunities for hiring, promotion, training, and development, for all employees, including but not limited to, Black, Indigenous, and people of color (BIPOC).
Telecommute option: This is a hybrid role requiring on-site work at our San Francisco office. Occasional travel within San Francisco may be required 
Job Description 
We are a small, mission-driven team leading responsible AI adoption across City government within DT.
We work on:<ul><li>
 Testing and making self-service AI tools available to other departments,</li><li>
Setting technical standards for safe and responsible AI use, and</li><li>
Building and experimenting with prototypes that demonstrate the potential of applied AI.</li></ul>
As our Applied AI Engineer, your primary focus will be designing and backend AI cloud infrastructure needed to power AI services. This includes building ingestion pipelines, managing vector databases, integrating LLM APIs, and ensuring backend systems are reliable, observable, scalable, and safe.
This role is hands-on, creative, and highly collaborative &mdash; ideal for someone who enjoys working at the intersection of technology, product, and impact.
Key Responsibilities:<ul><li>
Build and manage RAG infrastructure and other cloud tools as needed (e.g., ingestion pipelines, embedding services, retrieval APIs, orchestration).</li><li>
Deploy and maintain vector databases and integrate them with AI services.</li><li>
Develop APIs and backend services that connect prototypes to LLMs and retrieval systems.</li><li>
Implement observability practices including monitoring, logging, alerting, and performance metrics to ensure system reliability and transparency.</li><li>
Use frameworks like LangChain, LlamaIndex, and related libraries to orchestrate retrieval workflows, agents, and hybrid pipelines.</li><li>
Ensure system scalability and resilience, with production-ready practices.</li><li>
Collaborate with the AI Product Engineer to integrate backend services with front-end applications and user pilots.</li><li>
Contribute to standards for safe, responsible AI adoption (data governance, security, and compliance).</li><li>
Experiment with new backend, platform, and cloud tools to stay current with the fast-evolving AI ecosystem.</li></ul> 


Qualifications 
Education:
An associate degree in computer science, computer engineering, information systems, or a closely related field from an accredited college or university OR its equivalent in terms of total course credits/units [i.e., at least sixty (60) semester or ninety (90) quarter credits/units with a minimum of twenty (20) semester or thirty (30) quarter credits/units in one of the fields above or a closely-related field].
Experience:
One (1) year of experience analyzing, installing, configuring, enhancing, and/or maintaining the components of an enterprise network.
Additional experience as described above may be substituted for the required degree on a year-for-year basis (up to a maximum of two (2) years). One (1) year is equivalent to thirty (30) semester units/r forty-five (45) quarter units with a minimum of 10 semester / 15 quarter units in one of the fields above or a closely related field.
Completion of the 1010 Information Systems Trainee Program may be substituted for the required degree.
Desirable Qualifications: 
Must-Have Skills<ul><li>
Strong experience with backend/ platform engineering</li><li>
Experience building and managing RAG pipelines using vector databases and orchestration frameworks (LangChain, LlamaIndex, LangGraph).</li><li>
Hands-on experience with observability practices and tools</li><li>
Knowledge of cloud platforms (AWS, GCP, or Azure) and containerized deployments</li><li>
Ability to work collaboratively in a small, cross-functional team and move quickly on pilots.</li></ul>
Nice-to-Have Skills<ul><li>
Knowledge of search and ranking techniques (hybrid search, rerankers).</li><li>
Familiarity with data security, privacy, and compliance in government or regulated contexts.</li><li>
Background in ML/AI infrastructure (model serving, caching, fine-tuning workflows).</li><li>
Experience contributing to technical documentation and standards.</li></ul>
Who You Are<ul><li>
Motivated by public impact and eager to shape how AI can responsibly improve services for residents.</li><li>
A builder and experimenter who takes a human-centered approach and loves creating prototypes that make AI real and useful.</li><li>
Excited by the challenge of making AI safe, transparent, and practical in government.</li><li>
Flexible and collaborative, comfortable stepping outside your core skill set to help the team succeed.</li><li>
Keen to stay current with emerging technologies</li></ul>
Note: Applicants must meet the minimum qualification requirement by the final filing date unless otherwise noted.
One-year full-time employment is considered equivalent to 2000 hours (2000 hours of qualifying work experience is based on a 40hour work week). Any overtime hours that you work above forty (40) hours per week are not included in the calculation to determine full-time employment. 
Additional Information<ul><li> 
Information About the Hiring Process</li><li>
Conviction History</li><li>
Employee Benefits Overview</li><li>
Equal Employment Opportunity</li><li>
Disaster Service Worker</li><li>
ADA Accommodation</li></ul><ul><li>
Veterans Preference</li><li>
Right to Work</li><li>
Copies of Application Documents</li><li>
Diversity Statement</li></ul>
Applicants will receive a confirmation email from notification@careers.sf.gov that their online application has been received in response to every announcement for which they file. Applicants should retain this confirmation email for their records. Failure to receive this email means that the online application was not submitted or received.
Applicants may be contacted by email about this recruitment and, therefore, it is their responsibility to ensure that their registered email address is accurate and kept up-to-date. Also, applicants must ensure that email from CCSF is not blocked on their computer by a spam filter. To prevent blocking, applicants should set up their email to accept CCSF mail from the following addresses (@sfgov.org, @sfdpw.org, @sfport.com, @flysfo.com, @sfwater.org, @sfdph.org, @asianart.org, @sfmta.com, @sfpl.org, @dcyf.org, @first5sf.org, @famsf.org, @ccsf.edu, @smartalerts.info, and @smartrecruiters.com).
Exam Analyst Information: If you have any questions regarding this recruitment or application process, please contact the analyst at jason.wong3@sfgov.org<div></div>
The City and County of San Francisco encourages women, minorities and persons with disabilities to apply. Applicants will be considered regardless of their sex, race, age, religion, color, national origin, ancestry, physical disability, mental disability, medical condition (associated with cancer, a history of cancer, or genetic characteristics), HIV/AIDS status, genetic information, marital status, sexual orientation, gender, gender identity, gender expression, military and veteran status, or other protected category under the law.</div>

APPLIED AI ENGINEER (1042) - Department of Technology

Tesla

<div>What to Expect<div>
As a Software Engineer within the Autopilot AI Infrastructure team, you will work on reinforcing, optimizing, and scaling our infrastructure components supporting AI research activities for Autopilot and the Optimus.
At the core of our autonomy capabilities are neural networks that the research team is designing to train on very large amounts of data, across large-scale GPU clusters and our supercomputer Dojo. Robustly training these models at scale and in the shortest amount of time is critical to our mission.
We are building out the Machine Learning Platform that our engineers and leadership use to schedule, manage and monitor machine learning experiments, data pipelines and artifacts. With the ever-increasing size of our datasets and compute clusters, we are looking for an experienced backend engineer to help drive scalability improvements and new capabilities in the platform.</div> 
What You'll Do<div><ul><li>
Develop and deploy solutions to scale our infrastructure effectively in response to rapidly growing demands</li><li>
Drive implementation of best practices and monitoring systems to proactively detect and address issues in our production environment</li><li>
Work across the stack on tools and infrastructure empowering the machine learning team to be effective. This ranges from developing/running model training and evaluation code to back-end infrastructure to occasional front-end work</li><li>
Coordinate required resources with the team managing the cluster hardware to maintain high availability</li><li>
Work closely with the research team to understand requirements and priorities</li></ul></div> 

What You'll Bring<div><ul><li>
Expertise in designing scalable and durable distributed systems</li><li>
Strong knowledge of Python/Go and Linux</li><li>
Experience working with diverse backend infrastructure components (SQL / NoSQL databases, caching, message brokers, event streams, monitoring etc.)</li><li>
Hands-on experience with containerization and orchestration technologies (Docker, Kubernetes) and setting up CI/CD flows</li><li>
Knowledge of front-end development in React / strong product sense</li><li>
Knowledge of machine learning, computer vision, or neural networks</li><li>
Experience working with HPC clusters</li></ul></div> 

Compensation and Benefits<div>
Benefits</div><div>
Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:
<ul><li>Aetna PPO and HSA plans &gt; 2 medical plan options with $0 payroll deduction</li>
<li>Family-building, fertility, adoption and surrogacy benefits</li>
<li>Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution</li>
<li>Company Paid (Health Savings Account) HSA Contribution when enrolled in the High Deductible Aetna medical plan with HSA</li>
<li>Healthcare and Dependent Care Flexible Spending Accounts (FSA)</li>
<li>401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits</li>
<li>Company paid Basic Life, AD&amp;D, short-term and long-term disability insurance</li>
<li>Employee Assistance Program</li>
<li>Sick and Vacation time (Flex time for salary positions), and Paid Holidays</li>
<li>Back-up childcare and parenting support resources</li>
<li>Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft &amp; legal services, and pet insurance</li>
<li>Weight Loss and Tobacco Cessation Programs</li>
<li>Tesla Babies program</li>
<li>Commuter benefits</li>
<li>Employee discounts and perks program</li>
</ul></div><div>Expected Compensation</div><div>
$132,000 - $390,000/annual salary + cash and stock awards + benefits
Pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.</div> 
Tesla is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state or local laws. 
 
Tesla is also committed to working with and providing reasonable accommodations to individuals with disabilities. Please let your recruiter know if you need an accommodation at any point during the interview process.</div>

Backend Software Engineer, Machine Learning Platform, AI Infrastructure

Search 10000+ Ai infrastructure engineer jobs near you this November. New roles added regularly across leading industries. Apply today.