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<h3>Job Description</h3>
AI/ML Engineer – LLM Focus
 
Location: San Jose, CA
Experience: 6–8 Years
 
We are seeking a talented AI/ML Engineer with a strong background in Large Language Models (LLMs) and Artificial Intelligence to join our dynamic team in San Jose, CA. The ideal candidate will work collaboratively with global product and engineering teams to design and implement cutting-edge AI solutions that align with key business objectives.
 
&amp;#x1F527; Key Responsibilities:
<ul>
<li>Collaborate with product and engineering teams to design and implement LLM/AI-based solutions.</li>
<li>Develop and deploy AI/ML models that leverage the latest advances in machine learning and natural language processing.</li>
<li>Continuously evaluate and enhance current systems by analyzing user behavior using AI/ML methods.</li>
<li>Support and scale AI solutions across different products and platforms.</li>
<li>Stay up to date with the latest industry trends, tools, and technologies in AI, ML, and LLMs.</li>
</ul>
 
&amp;#x1F9E0; Key Skills &amp; Technologies:
<ul>
<li>Strong experience in AI/ML, Deep Learning, and Natural Language Processing (NLP).</li>
<li>Proficiency with LLMs such as OpenAI GPT, Google PaLM, Meta LLaMA, etc.</li>
<li>Experience with frameworks like TensorFlow, PyTorch, Hugging Face Transformers, etc.</li>
<li>Expertise in Python and ML libraries (NumPy, Pandas, Scikit-learn).</li>
<li>Experience in deploying models using cloud platforms like AWS, GCP, or Azure.</li>
<li>Strong understanding of MLOps, model versioning, and CI/CD pipelines.</li>
<li>Proven experience working in a product-focused engineering environment.</li>
</ul>
 
&amp;#x1F4DA; Education:
<ul>
<li>Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or a related field.</li>
</ul>

Machine Learning Engineer/AI

<h3>Job Description</h3>
Role Overview:
 
The Field Service Technician provides onsite repair and installation services for various OEM products, including desktops, laptops, and tablets. The role involves direct interaction with clients to address and resolve technical issues promptly and accurately.
 
Responsibilities:
<ul>
<li>Provide onsite hardware repair and installation for laptops, desktops, workstations, and tablets.</li>
<li>Perform maintenance, upgrades, and repairs of IT products.</li>
<li>Ensure all service level agreements (SLAs) are met.</li>
<li>Communicate effectively with clients and team members.</li>
<li>Prioritize and manage multiple technical issues simultaneously.</li>
<li>Complete administrative tasks related to each service call.</li>
<li>Follow company standards for security, safety, and quality.</li>
</ul>
 
Skills:
<ul>
<li>Ability to lift and move computer equipment up to 50 lbs.</li>
<li>Own a basic repair toolkit, PC, and mobile phone.</li>
<li>Strong customer support and communication skills.</li>
<li>Basic troubleshooting and break/fix skills for laptops and desktops.</li>
<li>Knowledge of operating systems, hardware, and standard software applications.</li>
<li>Ability to install, test, and configure desktop, laptop, and tablet systems.</li>
<li>Experience with software imaging and component replacements (e.g., memory, hard drives, SSDs, screens, keyboards).</li>
</ul>
 
Qualifications:
<ul>
<li>High school diploma or equivalent.</li>
<li>Relevant technical qualification and 6-12 months of work experience.</li>
<li>PC repair certifications preferred.</li>
<li>Experience with deskside support and ticket management tools is a bonus.</li>
</ul>
 
Accountabilities:
<ul>
<li>Complete required certifications for PC repairs.</li>
<li>Perform fault diagnosis and effective troubleshooting.</li>
<li>Maintain parts inventory and adhere to return deadlines.</li>
<li>Keep accurate real-time updates in the system.</li>
</ul>

Field Service Technician

<h3>Job Description</h3>
Coders Connect are working with a high-growth audio AI company solving real-world challenges with cutting-edge ML and DSP. Their elite clients include top-tier AI labs and FAANG companies—and now they’re expanding their ML team.
 
We’re hiring a Machine Learning Engineer who thrives on building production-grade ML systems, pipelines, and inference infrastructure. You’ll collaborate across product and data operations to deploy scalable solutions that transform audio into insight.
 
&amp;#x1F4CD; Location: San Francisco or New York City
 
&amp;#x1F9E9; What You’ll Be Doing
<ul>
<li>Design and implement advanced ML and DSP models for speech/audio</li>
<li>Build robust inference pipelines and APIs</li>
<li>Work cross-functionally to improve dataset quality and model performance</li>
<li>Own the ML roadmap and influence strategic direction</li>
</ul>
 
✅ What You Bring
<ul>
<li>Master’s degree in ML, data science, or engineering</li>
<li>Strong applied ML experience (audio or signal processing ideal)</li>
<li>Proven track record of deploying ML models in production</li>
<li>Python + PyTorch expertise; cloud experience (AWS/GCP)</li>
</ul>
 
&amp;#x1F3AF; Ideal For: Candidates who can translate ML research into real-world impact—especially in fast-moving, high-growth environments.

🤖 Machine Learning Engineer | SF or NYC | $250K Base + Equity

<h3>Job Description</h3>
LinkedIn is the world’s largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We’re also committed to providing transformational opportunities for our own employees by investing in their growth. 
We aspire to create a culture that’s built on trust, care, inclusion, and fun – where everyone can succeed. Join us to transform the way the world works.\n\nThis role will be based in Sunnyvale, San Francisco, Bellevue or New York City.\n\nAt LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.\n\nLinkedIn's Machine Learning Engineers are both data/research scientists and software engineers, who develop and implement machine learning models and algorithms. 
 Unlike other companies that separate these roles, our engineers work on projects from ideation to implementation. \nAs a Staff Engineer at LinkedIn, you will be responsible for the development and training of cutting-edge machine learning models and algorithms that can effectively leverage our members’ platform activities and industry trends to create personalized recommendations that are delivered to our members at the optimal moment. \n\nResponsibilities:\n• Work with BIG data, crunching millions of samples for statistical modeling, data mining, recommendation solutions\n• Write production quality code and influence the next generation of LinkedIn’s system\n• Collaborate with 10+ machine learning engineers to deliver impact on LinkedIn newsfeed\n• Build scalable AI innovations with foundation and infra partners\n\nBasic Qualifications:\n• Bachelor’s degree in Computer Science or related technical field or equivalent practical experience\n• 4+ years of industry experience in software design, development, and algorithm related solutions.\n• 4+ years experience in programming languages such as Java, Python, etc.\n• 4+ years experience with machine learning, data mining, and information retrieval or natural language processing \n\nPreferred Qualifications: \n• 6+ years of relevant machine learning experience\n• MS or PhD in Computer Science or related technical discipline\n• Experience with machine learning, optimization algorithms, deep-learning techniques\n• Experience developing large scale systems\n• Experience with Spark, Tensorflow and Java.\n• Previous leadership or mentorship experience is preferred\n• Ability to diagnose technical problems, debug code, and automate routine tasks\n• Analytical approach coupled with solid communication skills and a sense of ownership\n• Track record of producing papers in conferences such as KDD, WWW, WSDM, and Patenting Innovations\n\nSuggested Skills:\n• Experience leading engineers to tackle a large-scale AI problem\n• Strong technical background &amp; Strategic thinking\n• Experience in Machine Learning, Big Data and Deep Learning\n• Experience in GAI and/or LLMs\n\n\nYou will Benefit from our Culture:\nWe strongly believe in the well-being of our employees and their families. 
That is why we offer generous health and wellness programs and time away for employees of all levels.\n\nLinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $164,000-$268,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. 
This may be different in other locations due to differences in the cost of labor. \nThe total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit <a href="https://careers.linkedin.com/benefits" target="_blank">https://careers.linkedin.com/benefits</a>.\n\nEqual Opportunity Statement\n We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. 
LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. \n\n LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful.\n\n If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at <a href="mailto:accommodations@linkedin.com" target="_blank">accommodations@linkedin.com</a> and describe the specific accommodation requested for a disability-related limitation.\n\n Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. 
Examples of reasonable accommodations include but are not limited to:\n\n -Documents in alternate formats or read aloud to you \n -Having interviews in an accessible location\n -Being accompanied by a service dog\n -Having a sign language interpreter present for the interview\n\n A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response.\n\n LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information.\n\n Pay Transparency Policy Statement\n As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: <a href="https://lnkd.in/paytransparency" target="_blank">https://lnkd.in/paytransparency</a>.\n\n Global Data Privacy Notice for Job Candidates\n This document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: <a href="https://lnkd.in/GlobalDataPrivacyNotice" target="_blank">https://lnkd.in/GlobalDataPrivacyNotice</a>

Staff AI Engineer

<h3>Job Description</h3>
Applied AI Engineer - Early-Stage, High-Ownership Role in SF
San Francisco | In-Office | Early-Stage AI Startup | Backed by Top Investors
 
Ready to build, break, and scale with serious velocity?
 
We’re hiring a Founding AI/ML Engineer to join a founder-led AI startup that’s in blitz mode - shipping fast, scaling faster, and solving real-world problems with applied AI. They’ve got early traction, strong product-market fit, and now it’s all about throughput. That’s where you come in.
 
What you’ll do:
 
<ul>
<li>Build and ship AI-driven features and agentic systems from scratch</li>
<li>Work shoulder-to-shoulder with sharp engineers and even sharper founders</li>
<li>Get your hands dirty across the stack: from pipelines and infrastructure to model orchestration</li>
<li>Shape not just what gets built, but how it gets built - you'll define culture as much as code</li>
<li>Operate in a culture of speed, intensity, and obsession over quality</li>
</ul>
 
Why this role is different:
 
<ul>
<li>Ownership: You’ll have autonomy from day one - this is a true builder’s role</li>
<li>Real-world impact: This isn’t a research lab. You’ll ship code that gets used - fast</li>
<li>Cohort culture: Join a team of insanely driven peers who don’t blink at 5am standups</li>
<li>Growth: The pace is relentless, but so is the learning. You’ll level up quickly here</li>
</ul>
 
You might be a fit if you:
 
<ul>
<li>Have 3+ years of experience in data science, ML, or AI engineering (ex-founders welcome)</li>
<li>Know how to build end-to-end systems: data pipelines, ETL, infrastructure, and ML deployment</li>
<li>Have worked on AI agents, LLMs, or tools in the customer service/sales space</li>
<li>Thrive in early-stage chaos and want to help build a billion-dollar company from the ground up</li>
<li>Have a strong technical foundation (ideally a Master’s or equivalent experience in AI/ML-heavy projects)</li>
</ul>
 
If you’re ready to go full-send and build with a team that’s all-in - we want to hear from you.

Applied AI Engineer

<h3>Job Description</h3>
Engineer | Reimagine How Homes Get Built
&amp;#x1F4CD; Palo Alto, CA | Remote-friendly | Must be located in the U.S. | Equity-based role
 
 
Wonderwall Solutions is transforming fragmented processes — architecture, engineering, and construction — into a structured, product-driven experience for both builders and consumers
 
 
About the Role
 
This is a hybrid position at the intersection of mechanical systems and software infrastructure. We’re looking for someone who can think across domains and help shape systems that impact both the digital and physical layers of housing
 
 
Scope
 
Mechanical Engineering
<ul>
<li>Systematize construction and MEP logic into decision frameworks</li>
<li>Contribute to how site, structural, and regulatory factors inform design workflows</li>
<li>Help define technical patterns for scalable homebuilding</li>
<li>Bring field and engineering knowledge into core platform logic</li>
<li>Ensure decisions align with real-world construction, permitting, and supply constraints</li>
</ul>
 
Software Engineering
<ul>
<li>Design and implement backend systems that power the platform</li>
<li>Build tools and workflows that translate complex inputs into clear outputs</li>
<li>Work across data models, API logic, and internal infrastructure</li>
<li>Collaborate on product decisions and support pilot deployments</li>
<li>Contribute to clean, scalable codebases (Python preferred, but not required)</li>
</ul>
 
 
You Might Be:
<ul>
<li>A mechanical, civil, or structural engineer who also codes</li>
<li>Experienced in (or curious about) housing, zoning, or construction supply chains</li>
<li>A systems thinker who reduces complexity into modular logic</li>
<li>Independent, execution-oriented, and excited by product challenges</li>
<li>Motivated to build from first principles — not templates</li>
</ul>
 
 
Important Notes:
<ul>
<li>We do not provide H1B sponsorship, unless you have significant U.S.-based experience in the field</li>
<li>Must be located in the U.S. — remote or hybrid is welcome, but proximity to the San Francisco Bay Area is a strong plus</li>
<li>This is an equity-based role (not salaried at this stage)</li>
</ul>
 
 
To Apply
 
Send a short note to <a href="mailto:salomon.omer@wonderwall-solutions.com" target="_blank">salomon.omer@wonderwall-solutions.com</a>
Include relevant experience, GitHub or code samples, and a sentence or two on why you’re excited about building real-world systems
We prioritize clarity, originality, and execution over formal credentials

Engineer

<h3>Job Description</h3>
AI Engineer - San Francisco, CA (Hybrid) 
 
A Series A funded start up who are democratizing safe, trustworthy generative AI through their open-source ML data quality framework and production APIs that help organizations ensure reliable AI outputs at scale are looking for an AI Engineer to join their team.
 
What Will I Be Doing:
 
<ul>
<li>Design and build backend infrastructure to support real-time analysis, visualization, and remediation of AI outputs</li>
<li>Work on scalable and low-latency systems for evaluating AI-generated content</li>
<li>Prototype and develop new product features informed by cutting-edge research</li>
<li>Collaborate closely with data scientists and ML engineers to integrate insights and feedback into product development</li>
</ul>
 
What We're Looking For:
 
<ul>
<li>Senior/Staff-level engineer (5+ years software engineering experience)</li>
<li>Production systems experience building and maintaining user-dependent systems</li>
<li>Deep Python expertise</li>
<li>Experience building and maintaining production systems from the ground up</li>
<li>Solid understanding of distributed systems and scalable architecture</li>
<li>API design experience, ideally with intuitive developer-facing interfaces</li>
<li>Experience with Large Language Models </li>
</ul>
 
What's in it for me:
 
<ul>
<li>$150,000 - $300,000 salary range plus equity, with regular raise opportunities and relocation bonus to San Francisco.</li>
<li>Work directly with MIT PhD founders, with significant input on architecture decisions and opportunity to grow into technical leadership as they scale.</li>
<li>Unlimited PTO and sick days, plus 10 company holidays</li>
</ul>
 
Apply now for immediate consideration!

680 Engineering Jobs in San Lorenzo, CA, USA