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<div>San Francisco, California 94016 Posted February 24th, 2026
 <div></div>Looking for more job opportunities? Click here!</div>
 <div>Job Type: Contract
Job Category: IT
Job Description
Role: Sr. AI/ML Engineer<ul><li> Experience &ndash; 10+ Years</li><li> Location - San Francisco, CA &ndash; LOCALS Only</li></ul><div>
Required Qualifications 
<ul><li>Deep expertise in Machine Learning, Generative AI, LLMs, RAG, and AI orchestration.</li><li>Strong understanding of Azure OpenAI, AWS Bedrock, or similar platforms.</li><li>Experience deploying AI in regulated environments.</li><li>Hands-on architectural and engineering leadership capabilities.</li><li>Strong communication skills with VP/Senior Director stakeholders.</li></ul>
 Preferred Qualifications 
<ul><li>12+ years in AI/ML, data engineering, or digital transformation.</li><li>Prior experience leading enterprise AI programs.</li><li>Utility domain experience (wildfire, grid, operations).</li><li>Knowledge of Responsible AI frameworks (NIST AI RMF, ISO 42001).</li></ul> 

Roles &amp; Responsibilities 
Role Overview 
Utilities are accelerating their enterprise AI adoption across Operations, Customer Experience, Wildfire Safety, Regulatory, and IT. The AI Lead will serve as the strategic driver for enterprise AI transformation&mdash;defining vision, governance, enterprise architecture, and leading delivery of high-impact GenAI and ML solutions.</div><div> 
Key Responsibilities 
<ul><li>Define the enterprise AI vision, roadmap, and operating model.</li><li>Identify and prioritize AI/ML/GenAI opportunities across business units.</li><li>Drive design and deployment of AI solutions including consultation agents, hazard detection, regulatory Q&amp;A automation, and contact center assistants.</li><li>Establish AI governance, compliance, model risk management, and auditability frameworks.</li><li>Lead cross-functional AI programs spanning IT, Operations, Customer Care, Regulatory, Safety, and Field Ops.</li><li>Mentor and guide data scientists, ML engineers, architects, and product owners.</li><li>Promote AI literacy, change management, and best practices across the enterprise.</li></ul></div>
Required Skills
DEVOPS ENGINEER SENIOR EMAIL SECURITY ENGINEER</div>

Sr. AI/ML Engineer-4

<div>Site Name: Cambridge 300 Technology Square, London The Stanley Building, South San Francisco 611 Gateway Blvd 
Posted Date: Mar 2 2026 
At GSK we see a world in which advanced applications of Machine Learning and AI will allow us to develop transformational medicines using the power of genetics, functional genomics and machine learning. AI will also play a role in how we diagnose and use medicines to enable everyone to do more feel better and live longer. It is an ambitious vision that will require the development of products at the cutting edge of Machine Learning and AI.
The opportunities for machine learning extend to many other areas of our business, including medicine safety, manufacturing, and supply chain. To realize these opportunities, GSK has created a global Artificial Intelligence and Machine learning group (AI/ML), with locations in London, San Francisco, Boston, Philadelphia, and Heidelberg, to focus on the development and application of machine learning to problems of critical importance at GSK. We possess a world-leading data and computational environment (including specialist hardware) to enable large-scale, scientific experiments that exploit GSK&rsquo;s unique access to data.
By actively engaging with the machine learning community and publishing our research, code and models built on public data, the AI/ML group operates at the cutting-edge of machine learning research. To help us, we seek a passionate researcher who wishes to turn their talents to the application of causal machine learning to the healthcare sector. You will be working with multiple Research Engineers on building products to support multiple large-scale projects within AI/ML. In addition, the researcher will learn about the pharmaceutical industry and software engineering and translate their research into tools that aid discovery and development of transformational medicines and vaccines. You will have access to outstanding experts in biology, clinical and translational research, chemistry, (software) engineering, data science and machine learning; unrivalled data sources and GSK&rsquo;s state-of-the-art laboratory and compute infrastructure to help you develop and validate your machine learning research.
As a Machine Learning Engineer focusing on applications in oncology, you will be expected to:<ul><li>
Design and implement novel scientific approaches for biophysical modeling and foundation model-driven analysis of multi-modal clinical and genomic data for biomarker and target discovery to improve patient selection and enable next-generation assets.</li><li>
Design, develop, and implement analytical solutions using a variety of commercial and open-source tools (common tools include PyTorch and scikit-learn). &bull; Connect and collaborate with subject matter experts in biology, genomics, and medicine.</li><li>
Identify opportunities to apply the latest advancements in Machine Learning and Artificial Intelligence to build, test, and validate predictive models.</li><li>
Develop and embed automated and agentic processes for predictive model validation, deployment, and implementation.</li><li>
Deploy your algorithms to production to identify actionable insights from large databases.</li></ul><h1 class="jobSectionHeader">
Why you?
</h1>Basic Qualifications:
We are looking for professionals with these required skills to achieve our goals:<ul><li>
Master&rsquo;s degree in computer science, applied math, statistics, physics, systems biology, computational biology, bioinformatics, or related field</li><li>
Experience in Python programming and knowledge in machine learning, statistics, and applied math.</li><li>
Familiarity with modern machine learning methods (generative models, representation learning)</li><li>
Experience in building deep learning models, preferably with exposure to biophysical modeling, functional genomics, molecular and cellular biology or to modeling dynamical systems</li><li>
Experience with at least one Deep Learning framework such as PyTorch</li></ul>
Preferred Qualifications:
If you have the following characteristics, they would be a plus:<ul><li>
PhD in computer science, applied mathematics, statistics, physics, systems biology, computational biology, bioinformatics, or a related field.</li><li>
Experience in analyzing real-world and/or clinical data.</li><li>
Experience in incorporating agentic models into ML workflows</li><li>
Understanding of best practices in software engineering, including training and operating algorithms at scale, and production deployment of ML services.</li><li>
Knowledge of cancer biology and precision oncology.</li><li>
Excellent written and verbal communication skills.</li><li>
Ability to digest, synthesize, and implement innovative methods from scientific literature.</li><li>
Ability to solve complex problems using creative approaches, state-of-the-art tools, and best engineering practices.</li><li>
Ability to work autonomously and collaboratively as part of a team, both teaching and learning every day.</li><li>
High impact publications at venues such as NeurIPS, ICML, ICLR etc. would be a plus</li><li>
Publicaiton in natural sciences would be a plus</li></ul>
#LI-GSK
# GSKAIML<ul><li>If you are based in Cambridge, MA; Waltham, MA; Rockville, MD; or San Francisco, CA, the annual base salary for new hires in this position ranges $136,125 to $226,875.
</li></ul> 
The US salary ranges take into account a number of factors including work location within the US market, the candidate&rsquo;s skills, experience, education level and the market rate for the role. In addition, this position offers an annual bonus and eligibility to participate in our share based long term incentive program which is dependent on the level of the role. Available benefits include health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and paid caregiver/parental and medical leave. 
 
If salary ranges are not displayed in the job posting for a specific country, the relevant compensation will be discussed during the recruitment process.
Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.
Why GSK?
Uniting science, technology and talent to get ahead of disease together.
GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases &ndash; to impact health at scale.
People and patients around the world count on the medicines and vaccines we make, so we&rsquo;re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.
Should you require any adjustments to our process to assist you in demonstrating your strengths and capabilities contact us at HR.AmericasSC-CS@gsk.com where you can also request a call.
Please note should your inquiry not relate to adjustments, we will not be able to support you through these channels. However, we have created a Recruitment FAQ guide. Click the link where you will find answers to multiple questions we receive
GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.
Important notice to Employment businesses/ Agencies
GSK does not accept referrals from employment businesses and/or employment agencies in respect of the vacancies posted on this site. All employment businesses/agencies are required to contact GSK's commercial and general procurement/human resources department to obtain prior written authorization before referring any candidates to GSK. The obtaining of prior written authorization is a condition precedent to any agreement (verbal or written) between the employment business/ agency and GSK. In the absence of such written authorization being obtained any actions undertaken by the employment business/agency shall be deemed to have been performed without the consent or contractual agreement of GSK. GSK shall therefore not be liable for any fees arising from such actions or any fees arising from any referrals by employment businesses/agencies in respect of the vacancies posted on this site.
Please note that if you are a US Licensed Healthcare Professional or Healthcare Professional as defined by the laws of the state issuing your license, GSK may be required to capture and report expenses GSK incurs, on your behalf, in the event you are afforded an interview for employment. This capture of applicable transfers of value is necessary to ensure GSK&rsquo;s compliance to all federal and state US Transparency requirements. For more information, please visit the Centers for Medicare and Medicaid Services (CMS) website at https://openpaymentsdata.cms.gov/</div>

AI/ML Engineer

Call For Referral

<div>
 
 
 Machine Learning Engineer
 
 
 
 
 Work Mode:
 
 
 Remote
 
 
 
 
 Compensation:
 
 
 $100&ndash;$120 per hour
 
 
 
 
 Work Type:
 
 
 Hourly, Independent
 
 
 
 
 Role Overview
 
 
 
 This role supports the evaluation of
 
 advanced machine learning systems
 
 in collaboration with
 
 leading AI research initiatives
 
 . It is intended for
 
 experienced machine learning engineers and researchers
 
 who can contribute to the development of
 
 high-quality evaluation suites
 
 that measure AI performance on
 
 real-world machine learning engineering tasks
 
 .
 
 
 The work focuses on translating
 
 practical ML research and engineering workflows
 
 into
 
 structured benchmarks
 
 for
 
 frontier models
 
 . This is a
 
 project-based, fully remote
 
 opportunity for professionals with
 
 strong hands-on ML research and engineering experience
 
 .
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 
 Design and develop
 
 detailed evaluation suites for machine learning engineering tasks
 </li>
 <li>
 
 Evaluate AI-generated solutions
 
 across model training, debugging, optimization, and experimentation workflows
 </li>
 <li>
 
 Analyze and document
 
 system behavior, performance characteristics, and limitations
 </li>
 <li>
 
 Contribute to the creation of benchmarks
 
 that reflect real-world ML engineering practices
 </li>
 <li>
 
 Maintain high standards
 
 of technical accuracy, clarity, and consistency in all deliverables
 </li>
 </ul>
 
 
 Qualifications
 
 
 <ul>
 <li>
 
 3+ years
 
 of experience in machine learning engineering or applied ML research
 </li>
 <li>
 
 Hands-on experience
 
 with model development, experimentation, and evaluation
 </li>
 <li>
 
 Background in ML research
 
 in an industry or academic setting (strongly preferred)
 </li>
 <li>
 
 Strong ability
 
 to reason about ML system design choices and technical trade-offs
 </li>
 <li>
 
 Excellent written communication skills
 
 and
 
 high attention to technical detail
 
 </li>
 </ul>
 
 
 Work &amp; Payment Details
 
 
 <ul>
 <li>
 You will operate as an
 
 independent professional
 
 </li>
 <li>
 This is a
 
 fully remote
 
 role with a
 
 flexible schedule
 
 </li>
 <li>
 Projects may be
 
 extended, shortened, or concluded
 
 based on needs and performance
 </li>
 <li>
 The work does
 
 not involve access to confidential or proprietary information
 
 from any employer, client, or institution
 </li>
 <li>
 
 Payments are made weekly
 
 via
 
 Stripe or Wise
 
 , based on services delivered
 </li>
 <li>
 Candidates requiring
 
 H1-B or STEM OPT
 
 sponsorship are
 
 not supported
 
 at this time
 </li>
 </ul>
 
 
 Application &amp; Onboarding Process
 
 
 <ul>
 <li>
 
 Upload your resume
 
 </li>
 <li>
 
 AI interview:
 
 A short
 
 15-minute
 
 conversational session to understand your background, experience, and interest in the role
 </li>
 <li>
 
 Follow-up communication
 
 within a few days with next steps and onboarding details
 </li>
 </ul>
 
 
</div>

Machine Learning Engineer (Remote)  $100 –$120/hr

Aarki

<div>
 
 Who are we?
 
 
 
 Aarki is an AI-driven company specializing in mobile advertising solutions designed to fuel revenue growth. We leverage AI to discover audiences in a privacy-first environment through trillions of contextual bidding signals and proprietary behavioral models. Our audience engagement platform includes creative strategy and execution. We handle 5 million mobile ad requests per second from over 10 billion devices, driving performance for both publishers and brands. We are headquartered in San Francisco, CA, with a global presence across the United States, EMEA, and APAC.
 
 
 
 The role?
 
 
 
 We are seeking a motivated and detail-oriented Machine Learning Engineer to join our team. As an ML Engineer, you will be involved in designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP). You will work closely with Senior MLE and other team members to drive impactful machine learning projects and contribute to innovative solutions.
 
 
 
 What will you do?
 
 
 
 <ul>
 <li>
 Support the development of machine learning models to address challenges in programmatic advertising, such as predicting user responses, forecasting bid landscapes, and detecting fraud.
 </li>
 <li>
 Collaborate with senior data scientists and cross-functional teams (product, engineering, and analytics) to integrate models into production workflows.
 </li>
 <li>
 Analyze the impact of integrating new data sources and features into our models.
 </li>
 <li>
 Build and maintain data pipelines to process and prepare large datasets for model training and evaluation.
 </li>
 <li>
 Contribute ideas and assist in testing new tools, methodologies, and technologies to improve our machine learning capabilities.
 </li>
 <li>
 Document experiments, assumptions, and outcomes; maintain reproducibility
 
 
 </li>
 </ul>
 
 What are we looking for?
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Mathematics, Physics, Computer Science, or a related technical field.
 </li>
 <li>
 At least 2 years of professional experience in machine learning, statistical analysis, and data analysis.
 </li>
 <li>
 Experience with machine learning techniques such as regression, classification, and clustering.
 </li>
 <li>
 Proficiency in Python and SQL and familiarity with big data tools (e.g., Spark) and ML libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).
 </li>
 <li>
 Strong grasp of probability, statistics, and data analysis principles.
 </li>
 <li>
 Ability to work effectively in a team environment, with good communication skills to explain complex concepts to diverse stakeholders.
 
 
 </li>
 </ul>
 Nice-to-Have
 
 
 <ul>
 <li>
 Familiarity with system programming languages including C++ and Rust is a plus.
 </li>
 <li>
 Exposure to online inference systems, gRPC/REST model endpoints, or streaming features (Kafka/Flink)
 </li>
 <li>
 Ad-tech familiarity: auction dynamics, pacing, fraud signals, creative personalization.
 </li>
 </ul>
</div>

Machine Learning Engineer

Attentive.ai

<div>
 
 About Attentive.ai
 
 
 
 Attentive.ai is transforming the field services and construction industries with our flagship AI solution - Beam AI. Our platform empowers businesses to double their bidding capacity and accelerate growth through automation and intelligent insights.
 
 
 More than
 
 1k+ businesses
 
 across the U.S. and Canada already use our products to boost sales velocity and streamline operations. We have raised
 
 $30.5M in Series B funding
 
 , accelerating our mission to make advanced AI tools accessible, practical, and impactful in the real world. We are proudly Backed by Insight Partners, Peak XV (Surge), InfoEdge, Tenacity and Vertex Ventures.
 
 
 
 Position Description
 
 
 
 As an
 
 AI/ML Research Scientist,
 
 you will be an integral part of our AI research team focused on transforming the construction industry through cutting-edge deep learning, computer vision and NLP technologies. You will contribute to the development of intelligent systems for automated construction take-off and estimation by working with unstructured data such as blueprint, drawings (including SVGs), and PDF documents.
 
 
 In this role, you will support the end-to-end lifecycle of AI-based solutions &mdash; from prototyping and experimentation to deployment in production. Your contributions will directly impact the scalability, accuracy, and efficiency of our products.
 
 
 
 Roles &amp; Responsibilities
 
 
 
 <ul>
 <li>
 Build and deploy ML models for parsing and reasoning over construction blueprint PDFs - working with image, text and vector graphics modalities
 </li>
 <li>
 Design data pipelines for training, validation, and continuous improvement.
 </li>
 <li>
 Improve model accuracy, latency, and scalability for production workloads.
 </li>
 <li>
 Contribute to system architecture decisions for ML deployment and monitoring.
 </li>
 <li>
 Collaborate with cross-functional teams including software engineers, ML researchers, and product teams
 </li>
 <li>
 Write clean, scalable, and production-ready code
 
 
 </li>
 </ul>
 
 Skills &amp; Requirements
 
 
 
 <ul>
 <li>
 3&ndash;5 years of experience in applied AI/ML and research, preferably with focus on computer vision.
 </li>
 <li>
 PhD or Master's degree in deep learning, coupled with research experience focused on image modalities.
 </li>
 <li>
 Experience working with document understanding, OCR pipelines, or structured extraction systems is a plus.
 </li>
 <li>
 Deep understanding of unsupervised learning techniques like clustering, dimensionality reduction, and representation learning.
 </li>
 <li>
 Proficiency in Python and ML frameworks such as PyTorch, OpenCV, TensorFlow, and HuggingFace Transformers.
 </li>
 <li>
 Hands-on experience with model optimization techniques (e.g., quantization, pruning, knowledge distillation)
 </li>
 <li>
 Familiarity with LLM based systems and architectures
 </li>
 <li>
 Comfortable working in a fast-moving, ownership-driven environment.
 
 
 </li>
 </ul>
 
 Why Work With Us?
 
 
 
 <ul>
 <li>
 Be part of a visionary team building a first-of-its-kind AI solution for the construction industry.
 </li>
 <li>
 Exposure to real-world AI deployment and cutting-edge research in vision and multimodal learning.
 </li>
 <li>
 Culture that encourages ownership, innovation, and growth.
 </li>
 <li>
 Opportunities for fast learning, mentorship, and career progression.
 </li>
 </ul>
</div>

AI/ML Research Scientist

Zendesk

<div><h2 class="jobSectionHeader">Job Description
</h2>Role: Machine Learning Engineer
TBH#:
Location: US 
 
Zendesk&rsquo;s people have one goal in mind: to make Customer Experience better. 
 
The Enterprise Machine Learning team drives organizational value through scalable ML solutions and data-driven insights, fundamentally changing how business decisions are made. We collaborate closely with stakeholders, applying the latest advances in machine learning, deep learning, and large language models (LLMs) to create highly impactful outcomes. Our commitment is to advance the state of AI, statistical modeling, and robust system design to enhance and expand our core business capabilities.
<h3 class="jobSectionHeader">Role Overview
</h3>As a Machine Learning Engineer, you will serve as a technical and strategic member within the team, driving the development and deployment of advanced data science and machine learning solutions&mdash;particularly those harnessing LLMs and deep learning. You will architect and scale ML systems, foster effective cross-functional collaborations, and ensure that business value is embedded in every technical decision. Your business acumen allows you to translate complex analytical approaches into actionable insights and stakeholder-friendly narratives, strengthening partnership and adoption across the enterprise.
<h3 class="jobSectionHeader">Key Responsibilities
</h3><ul><li>Drive the design, development, and deployment of advanced ML and AI solutions, with an emphasis on large language models (LLMs), deep learning architectures, and sophisticated statistical modeling.
</li><li>Build scalable, robust data science systems&mdash;from data ingestion, data curation, data modeling to algorithm development, model deployment and monitoring&mdash;meeting enterprise-grade performance, reliability, and compliance standards.
</li><li>Act as a subject matter expert, collaborating with data scientists, ML engineers, analysts, and business stakeholders to understand needs, define requirements, and deliver practical solutions with measurable business impact.
</li><li>Effectively articulate complex technical concepts to non-technical partners, bridging gaps between technical teams and business operations for maximum results.
</li><li>Drive adoption of best practices in MLOps, including CI/CD pipelines, containerization, orchestration, observability, and reproducibility.
</li><li>Oversee and enhance the integrity, security, and compliance of all data science workflows and contracts.
</li><li>Stay abreast of the latest industry advancements in ML, LLMs, deep learning, cloud data engineering, and MLOps solutions (AWS, Kubernetes, Snowflake, etc.).
</li><li>Fostering technical excellence and ensuring alignment with business objectives.
</li></ul><h3 class="jobSectionHeader">What We&rsquo;re Looking For
</h3><ul><li>Education &amp; Experience:
<ul><li>3+ years&rsquo; experience in Data Science, Machine Learning, or a related field
</li><li>BA/BS in Computer Science, Data Science, or related discipline (advanced degree is highly preferred)
</li></ul></li><li>Technical Expertise:
<ul><li>Deep expertise in statistical modeling, machine learning, and deep learning (including practical experience with LLMs and transformers)
</li><li>Strong programming skills (Python preferred; Java, Scala, or similar also valued)
</li><li>Proven ability to build and optimize scalable data science solutions&mdash;end-to-end&mdash;from data pipelines (dbt, Astronomer, Snowflake, AWS) to deployment and monitoring (Docker, Kubernetes, CI/CD, MLOps best practices)
</li><li>Experience handling and analyzing large datasets, with a preference for experience in cloud data warehouses (Snowflake)
</li></ul></li><li>Business Acumen:
<ul><li>Demonstrated success in translating business needs into analytical solutions, driving quantifiable impact
</li><li>Strong stakeholder engagement skills, with a track record of building trusted business partnerships and driving adoption of data science initiatives
</li></ul></li><li>Communication &amp; Collaboration:
<ul><li>Exceptional ability to simplify and communicate complex data science concepts to technical and non-technical audiences alike
</li><li>Experience working cross-functionally with engineers, analysts, and product leaders
</li><li>Steadfast commitment to continuous learning, collaboration, and fostering an inclusive, innovative team environment
</li></ul></li></ul><h3 class="jobSectionHeader">Why You&rsquo;ll Thrive Here
</h3><ul><li>Opportunity to develop and scale of LLM and deep learning solutions with real-world business impact
</li><li>An environment that values innovation, ownership, and professional growth
</li><li>The chance to work on high-visibility, high-impact projects at scale alongside a passionate multidisciplinary team 
</li></ul> 
 
Zendesk builds software for better customer relationships. It empowers organizations to improve customer engagement and better understand their customers. Zendesk products are easy to use and implement. They give organizations the flexibility to move quickly, focus on innovation, and scale with their growth. Based in San Francisco, Zendesk has operations in the United States, Europe, Asia, Australia, and South America. Learn more at www.zendesk.com . 
 
Individuals seeking employment at Zendesk are considered without regards to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, or sexual orientation.
The US annualized base salary range for this position is $206,000.00-$308,000.00. This position may also be eligible for bonus, benefits, or related incentives. While this range reflects the minimum and maximum value for new hire salaries for the position across all US locations, the offer for the successful candidate for this position will be based on job related capabilities, applicable experience, and other factors such as work location. Please note that the compensation details listed in US role postings reflect the base salary only (or OTE for commissions based roles), and do not include bonus, benefits, or related incentives.
Hybrid: In this role, our hybrid experience is designed at the team level to give you a rich onsite experience packed with connection, collaboration, learning, and celebration - while also giving you flexibility to work remotely for part of the week. This role must attend our local office for part of the week. The specific in-office schedule is to be determined by the hiring manager.
The intelligent heart of customer experience
Zendesk software was built to bring a sense of calm to the chaotic world of customer service. Today we power billions of conversations with brands you know and love.
Zendesk believes in offering our people a fulfilling and inclusive experience. Our hybrid way of working, enables us to purposefully come together in person, at one of our many Zendesk offices around the world, to connect, collaborate and learn whilst also giving our people the flexibility to work remotely for part of the week.
As part of our commitment to fairness and transparency, we inform all applicants that artificial intelligence (AI) or automated decision systems may be used to screen or evaluate applications for this position, in accordance with Company guidelines and applicable law.
Zendesk is an equal opportunity employer, and we&rsquo;re proud of our ongoing efforts to foster global diversity, equity, &amp; inclusion in the workplace. Individuals seeking employment and employees at Zendesk are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability, military or veteran status, or any other characteristic protected by applicable law. We are an AA/EEO/Veterans/Disabled employer. If you are based in the United States and would like more information about your EEO rights under the law, please click here .
Zendesk endeavors to make reasonable accommodations for applicants with disabilities and disabled veterans pursuant to applicable federal and state law. If you are an individual with a disability and require a reasonable accommodation to submit this application, complete any pre-employment testing, or otherwise participate in the employee selection process, please send an e-mail to peopleandplaces@zendesk.com with your specific accommodation request.</div>

Senior Machine Learning Engineer

Workato

<div>
 
 About Workato
 
 
 
 Workato transforms technology complexity into business opportunity. As the leader in enterprise orchestration, Workato helps businesses globally streamline operations by connecting data, processes, applications, and experiences. Its AI-powered platform enables teams to navigate complex workflows in real-time, driving efficiency and agility.
 
 
 Trusted by a community of 400,000 global customers, Workato empowers organizations of every size to unlock new value and lead in today&rsquo;s fast-changing world. Learn how Workato helps businesses of all sizes achieve more at workato.com.
 
 
 
 Why join us?
 
 
 
 Ultimately, Workato believes in fostering a
 
 flexible, trust-oriented culture that empowers everyone to take full ownership of their roles
 
 . We are driven by
 
 innovation
 
 and looking for
 
 team players
 
 who want to actively build our company.
 
 
 But, we also believe in
 
 balancing productivity with self-care
 
 . That&rsquo;s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives.
 
 
 If this sounds right up your alley, please submit an application. We look forward to getting to know you!
 
 
 
 Also, Feel Free To Check Out Why
 
 
 
 <ul>
 <li>
 Business Insider named us an &ldquo;enterprise startup to bet your career on&rdquo;
 </li>
 <li>
 Forbes&rsquo; Cloud 100 recognized us as one of the top 100 private cloud companies in the world
 </li>
 <li>
 Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America
 </li>
 <li>
 Quartz ranked us the #1 best company for remote workers
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 We are seeking a product-minded
 
 Software Engineer
 
 to join our San Francisco team focused on building the next generation of developer products. This role is at the forefront of innovation, specifically creating tools and platforms for developers who are building LLM and Agentic applications. You will be instrumental in shaping the future of how developers interact with and build on top of Workato's ecosystem in the age of AI. You will collaborate closely with product, engineering, and developer relations teams to deliver robust, scalable, and intuitive services. This role requires a high technical bar, plus an emphasis on developer ergonomics, so we can deliver a delightful developer experience. You will also be responsible to:
 
 
 <ul>
 <li>
 Design, build, and maintain robust, scalable, and high-quality developer-facing products and APIs for LLM and Agentic application development.
 </li>
 <li>
 Collaborate closely with product managers, designers, developer relations and other engineers to translate developer needs and product requirements into elegant technical solutions.
 </li>
 <li>
 Write clean, maintainable, and well-tested code, and contribute to a high standard of engineering excellence within the team.
 </li>
 <li>
 Implement and improve validation, monitoring, and observability for ML services within the sandbox environment.
 </li>
 <li>
 Drive the full development lifecycle: from ideation and architecture to deployment and continuous improvement.
 </li>
 <li>
 Continuously evaluate and optimize existing implementations for performance, scalability, and developer usability.
 </li>
 <li>
 Identify and resolve bottlenecks, bugs, and technical challenges in a fast-paced, iterative environment.
 </li>
 <li>
 Conduct code reviews and mentor team members to uphold high engineering standards.
 </li>
 <li>
 Stay at the cutting edge of AI, LLMs, and developer tooling, bringing new ideas and technologies to the team.
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 Qualifications / Experience / Technical Skills
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, Information Systems, or equivalent industry experience.
 </li>
 <li>
 3+ years of experience of professional software development experience, with a proven track record of shipping high-quality products.
 </li>
 <li>
 You are a product-minded engineer who thinks deeply about the end-user. You have strong opinions about what makes a great developer experience.
 </li>
 <li>
 You have experience building developer-facing products, APIs, SDKs, or CLIs.
 </li>
 <li>
 You are proficient in one or more modern programming languages such as Go, Python, Ruby, or JavaScript and hands-on experience with LLM models.
 </li>
 <li>
 Proven track record of deploying and maintaining ML services in production environments is a strong plus.
 </li>
 <li>
 Solid understanding of API design, developer tooling, software architecture, data structures, and algorithms.
 </li>
 <li>
 LLMops/MLops experience is a strong plus, especially in developer-facing products.
 </li>
 <li>
 Experience building or supporting developer platforms, APIs, or sandbox environments is highly desirable.
 
 
 </li>
 </ul>
 
 Soft Skills / Personal Characteristics
 
 
 
 <ul>
 <li>
 Excellent written and verbal communication skills in English.
 </li>
 <li>
 Collaborative team player with a passion for empowering developers and improving developer experience.
 </li>
 <li>
 Adaptable, proactive, and creative&mdash;comfortable working in a dynamic, startup-like environment.
 </li>
 <li>
 Strong problem-solving skills and a continuous improvement mindset.
 
 
 </li>
 </ul>
 
 (REQ ID: 2242)
 
</div>

Software Engineer - Developer Products (AI)

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