machine learning engineer

Software Engineer, Machine Learning RecSys

Databricks

<div><h1 class="jobSectionHeader"><b>Staff Machine Learning Engineer, CustomerLake (ML/LLM)</b></h1>
<p><i>RDQ427R109</i></p><p><br>
</p><p>At Databricks, we are passionate about enabling data teams to solve the world's toughest problems &mdash; from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best Data Intelligence Platform so our customers can use deep data insights to improve their business. Founded by engineers &mdash; and customer obsessed &mdash; we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.</p><p><br>
</p><p>As one of the first engineers in the NYC Engineering office, you'll join a small, nimble team building new products from the ground up. We're building CustomerLake, the Customer Data Platform on Databricks, to bring enterprise-grade ML and AI personalization to every company whose data already lives on Databricks. The best B2C and B2B brands have historically relied on in-house ML/AI teams to power personalization, recommendations, churn and lifetime-value modeling, and audience targeting. Our goal is to deliver that same capability to companies that don't have an in-house team but already have their data in order on Databricks. This is a true 0-to-1 environment, combining the excitement of a startup with the resources of a tech leader like Databricks.</p><p><br>
</p><p><b>The impact you'll have:</b></p>
<ul><li>Evaluate ML and LLM approaches for CustomerLake's personalization use cases, push the models and algorithms forward, and continuously improve quality over time</li>
<li>Go deep on how models behave in production: inspect individual traces, understand how the models reason, and tune and improve from there</li>
<li>Build the platform and evaluation framework that let CustomerLake customers optimize for real business value such as purchases, retention, and product usage, not vanity metrics like email opens and clicks</li>
<li>Push the team toward new directions and novel methods worth tackling, not just optimizing what already exists</li>
<li>Partner closely with product management, engineering, and design to turn ambiguous customer problems into scalable, trustworthy solutions</li>
<li>Set the technical foundation and best practices for our ML/AI personalization work as we grow this into several roles across our products over the next 1-2 years</li></ul><br>
<p></p><p><b>What we look for:</b></p>
<ul><li>10+ years of engineering experience, with a strong foundation across the full loop of shipping and improving ML/AI products</li>
<li>Hands-on experience building and evaluating ML models and/or LLM systems for real product or business use cases; your understanding is practical, not purely academic, and you can make models work well inside a product</li>
<li>Experience with personalization based on customer behavior (ideal) or transactions (acceptable), such as recommendations, targeting, churn, or lifetime-value modeling</li>
<li>Proficiency in Python and modern ML frameworks (e.g., PyTorch), with hands-on experience in model evaluation and monitoring AI quality in production</li>
<li>Familiarity with LLMs and generative AI, including techniques like retrieval-augmented generation (RAG), prompt design, fine-tuning, and evaluation</li>
<li>A demonstrated product mindset, with the ability to translate ambiguous customer problems into scrappy MVPs and iterate quickly based on data and user feedback</li>
<li>High ownership and bias for action in 0-to-1 environments: comfortable making pragmatic trade-offs, operating with incomplete information, and driving projects from idea through launch and adoption</li></ul><br>
<p></p><p><b>Nice to have:</b></p>
<ul><li>Experience in martech, ideally a go-to-market or business use case with an analytical (rather than purely transactional) angle</li>
<li>An academic or research background that can help us innovate and develop novel methods</li></ul><br>
<p></p><div><div><div><p><b>Pay Range Transparency</b></p>
<p>Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.<br>
<br>
</p></div><div>Local Pay Range</div>
<div>$192,000&mdash;$260,000 USD
</div></div></div><div><p><b>About Databricks</b></p>
<p>Databricks is the data and AI company. More than 10,000 organizations worldwide &mdash; including Comcast, Cond&eacute; Nast, Grammarly, and over 50% of the Fortune 500 &mdash; rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark&trade;, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
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<br>
<b>Benefits
</b><br>
<br>
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.<br>
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</p><p><b>Our Commitment to Diversity and Inclusion</b></p>
<p>At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.</p>
<p><b>Compliance</b></p>
<p><b>If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.</b></p></div></div>

Staff Software Engineer - AI/ML

The New York Times

<div><div><div><div><div><div><p><b>The </b><b>mission</b><b> of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It's why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It's why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it's why our business strategy centers on making journalism so good that it's worth paying for.</b></p>
</div>
</div></div></div></div><p><b>About the Role, Mission or Department Overview</b></p>
<p>
The New York Times is hiring a Machine Learning Scientist to join the New A.I. Products &amp; Platforms mission. We are a team building the next generation of reader-facing A.I. experiences for one of the world's most trusted news organizations.</p><br>
<p></p>
<p>
You will join a team of ML scientists developing embedding models and retrieval algorithms to power new A.I. experiences across our products. You will design and train embedding models for representation learning and fine-tune language models for custom use cases and content enrichment. Your work will allow teams across the company to build, deploy, and manage applications that use large language models (LLMs) to promote our journalism and our business. You will report to our Director, Machine Learning. This is a hybrid remote/in-office role.</p><br>
<p></p>
<p><b>
Responsibilities:</b></p>
<ul>
<li><p>You will design and train embedding models for representation learning, for example using transformer encoders and Two Tower architectures.</p>
</li>
<li><p>You will fine-tune and evaluate language models for custom use cases and content enrichment.</p>
</li>
<li><p>You will contribute to shared practices around evaluation, responsible A.I. use, and what &quot;good&quot; is inside an organization where judgment and independence are important</p>
</li>
<li><p>You will implement and deploy machine learning and AI research with robustness and reproducibility, with consideration of risks and trade-offs</p>
</li>
<li><p>You will adapt or develop ML and AI algorithms in cases when existing techniques are insufficient, while implementing simple approaches</p>
</li>
<li><p>You will communicate complex ideas in machine learning and AI while collaborating with all kinds of colleagues in engineering, analytics, product management, marketing, editorial, and executive leadership groups</p>
</li>
<li><p>Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.</p></li></ul><br>
<p>
</p><p><b>Basic Qualifications:</b></p>
<ul>
<li><p>PhD, MS + 2 years experience, or 3+ years work experience in machine learning, statistics, computational social science, applied mathematics, or another quantitative/computational discipline</p>
</li>
<li><p>2+ years experience with open source machine learning or statistical analysis tools</p>
</li>
<li><p>2+ years coding experience in Python</p>
</li>
<li><p>2+ years experience in SQL and manipulating large structured or unstructured datasets for analysis</p>
</li>
<li><p>1+ years of experience with deep learning architectures, fine-tuning, embeddings and Pytorch or Tensorflow</p></li></ul><br>
<p>
</p><p><b>Preferred Qualifications:</b></p>
<ul>
<li><p>1+ years of experience with information retrieval or search systems</p>
</li>
<li><p>1+ years of experience translating ambiguous business questions into machine learning problems</p>
</li>
<li><p>1+ years of experience building data products, either internal or consumer-facing</p>
</li>
</ul><p>REQ-020337</p><p></p><div><p><br>
For roles in the U.S., dependent on your role, you may be eligible for variable pay, such as an annual bonus and restricted stock. Benefits may include medical, dental and vision benefits, Flexible Spending Accounts (F.S.A.s), a company-matching 401(k) plan, paid vacation, paid sick days, paid parental leave, tuition reimbursement and professional development programs.</p>
<p>
For roles outside of the U.S., information on benefits will be provided during the interview process.</p>
<p>
We're excited to learn more about you and your experience. To keep our hiring process as fair and authentic as possible, we ask that you submit your own work and not use GenAI tools to generate substantive content during the application and interview process.</p>
<p>
If you're an Engineering candidate, we'll let you know what specific GenAI tools you are permitted to use for your technical assessment.</p>
<p>
The New York Times Company is committed to being the world's best source of independent, reliable and quality journalism. To do so, we embrace a diverse workforce that has a broad range of backgrounds and experiences across our ranks, at all levels of the organization. We encourage people from all backgrounds to apply.</p>
<p>
We are an Equal Opportunity Employer and do not discriminate on the basis of an individual's sex, age, race, color, creed, national origin, alienage, religion, marital status, pregnancy, sexual orientation or affectional preference, gender identity and expression, disability, genetic trait or predisposition, carrier status, citizenship, veteran or military status and other personal characteristics protected by law. All applications will receive consideration for employment without regard to legally protected characteristics. The U.S. Equal Employment Opportunity Commission (EEOC)'s Know Your Rights Poster is available here.</p>
<p>
The New York Times Company will provide reasonable accommodations as required by applicable federal, state, and/or local laws. Individuals seeking an accommodation for the application or interview process should email reasonable.accommodations@nytimes.com. Emails sent for unrelated issues, such as following up on an application, will not receive a response.</p>
<p>
The Company encourages those with criminal histories to apply, and will consider their applications in a manner consistent with applicable &quot;Fair Chance&quot; laws, including but not limited to the NYC Fair Chance Act, the Los Angeles Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.</p>
<p>
For information about The New York Times' privacy practices for job applicants click here.</p>
<p>
Please beware of fraudulent job postings. Scammers may post fraudulent job opportunities, and they may even make fraudulent employment offers. This is done by bad actors to collect personal information and money from victims. All legitimate job opportunities from The New York Times will be accessible through The New York Times careers site. The New York Times will not ask job applicants for financial information or for payment, and will not refer you to a third party to do so. You should never send money to anyone who suggests they can provide employment with The New York Times.</p>
<p>
If you see a fake or fraudulent job posting, or if you suspect you have received a fraudulent offer, you can report it to The New York Times at NYTapplicants@nytimes.com. You can also file a report with the Federal Trade Commission or your state attorney general.</p></div></div><p></p>

Machine Learning Scientist, New AI Products and Platforms

T-Mobile

<div><p>At T-Mobile, we invest in YOU! Our Total Rewards Package ensures that employees get the same big love we give our customers. All team members receive a competitive base salary and compensation package - this is Total Rewards. Employees enjoy multiple wealth-building opportunities through our annual stock grant, employee stock purchase plan, 401(k), and access to free, year-round money coaches. That&rsquo;s how we&rsquo;re UNSTOPPABLE for our employees!</p><p></p>
At T-Mobile Advertising Solutions, we're building privacy-first advertising products powered by advanced machine learning, large-scale data processing, and cloud technologies. Our proprietary algorithms enable rich consumer insights, intelligent audience solutions, and measurable performance for advertisers while maintaining a strong commitment to consumer privacy.<br>
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We are seeking a creative, and curious Senior Applied Scientist to join our team. In this role, you'll work at the intersection of machine learning, software engineering, and big data, building AI and ML systems that directly impact our customers and business. You'll collaborate with engineers, data scientists, product managers, and other stakeholders to solve complex problems and deliver innovative solutions at scale.<br>
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We embrace Lean Development principles, iterative experimentation, continuous learning, and a strong build-measure-learn feedback culture. The work you do will directly shape the future of our products and technologies.<p></p><div><div><div><div><div><div><div><div><div><p><b>
Job Responsibilities</b>:</p><ul><li><p>
Lead the end-to-end development of machine learning and data products aligned to business objectives, from problem framing through deployment and monitoring.</p></li><li><p>
Build scalable data, training, and inference pipelines using distributed processing and cloud technologies.</p></li><li><p>
Apply statistical methods, experimentation, and validation frameworks to ensure solution quality and business impact.</p></li><li><p>
Write production-quality code and contribute to engineering best practices, including testing, CI/CD, and observability.</p></li><li><p>
Collaborate across engineering, product, and business teams while leading other engineers and data scientists.
</p></li></ul><p></p><p><b>Education and Work Experience</b>:</p><ul><li><p>
Bachelor's Degree plus 5 years of related work experience OR Advanced degree with 3 years of related experience (Required)</p></li><li><p>
Acceptable areas of study include Quantitative Discipline (math, statistics, economics, computer science, physics, engineering, etc.) (Required)</p></li><li><p>
4-7 years experience building and deploying machine learning and deep learning solutions at scale; familiarity with MLOps and DevOps practices and tools. (Required)</p></li><li><p>
4-7 years Experience working within big data architecture, modern analytical data platforms, and large-scale data warehousing technologies (e.g. BigQuery, Snowflake, Redshift) (Required)</p></li><li><p>
4-7 years Experience working with large-scale distributed data systems and cloud platforms (e.g. SQL, Python, Scala, AWS) (Required)</p></li><li><p>
4-7 years Experience solving complex data, machine learning, or algorithmic challenges in production environment using modern engineering practices.(Required)</p></li></ul><p><b><br>
Knowledge, Skills and Abilities</b>:</p><ul><li><p>
Strong background in AI/ML, data structures, statistical modeling, optimization algorithms, big data, and design thinking.</p></li><li><p>
Advanced knowledge of cloud-based services (GCP, AWS)</p><p>
and Python, PySpark and related Python libraries (e.g. pandas, scikit-learn, scipy, numpy) for advanced data science tasks.</p></li><li><p>
Hands-on implementation and architectural familiarity with streaming data, relational and non-relational databases, and distributed processing technologies.</p></li><li><p>
Experience operating production machine learning and data systems in cloud and containerized environments.</p></li><li><p>
Experience in AdTech and GIS or geospatial data processing is a plus.</p></li></ul></div></div></div></div></div></div></div></div></div><p></p><ul><li><p>
At least 18 years of age</p></li><li><p>
Legally authorized to work in the United States</p></li></ul><p></p><p><b>
Travel</b>:<br>
Travel Required (Yes/No): No<br>
<br>
<b>DOT Regulated</b>:<br>
DOT Regulated Position (Yes/No): No<br>
Safety Sensitive Position (Yes/No): No</p><p></p>
Base Pay Range: $116,500 - $210,100<p></p>
Corporate Bonus Target: 15%<p></p><p>
The pay range above is the general base pay range for a successful candidate in the role. The successful candidate&rsquo;s actual pay will be based on various factors, such as work location, qualifications, and experience, so the actual starting pay will vary within this range.</p><p></p>
At T-Mobile, employees in regular, non-temporary roles are eligible for an annual bonus or periodic sales incentive or bonus, based on their role. Most Corporate employees are eligible for a year-end bonus based on company and/or individual performance and which is set at a percentage of the employee&rsquo;s eligible earnings in the prior year. Certain positions in Customer Care are eligible for monthly bonuses based on individual and/or team performance. To find the pay range for this role based on hiring location, click here.<p></p><p>
At T-Mobile, our benefits exemplify the spirit of One Team, Together! A big part of how we care for one another is working to ensure our benefits evolve to meet the needs of our team members. Full and part-time employees have access to the same benefits when eligible. We cover all of the bases, offering medical, dental and vision insurance, a flexible spending account, 401(k), employee stock grants, employee stock purchase plan, paid time off and up to 12 paid holidays - which total about 4 weeks for new full-time employees and about 2.5 weeks for new part-time employees annually - paid parental and family leave, family building benefits, back-up care, enhanced family support, childcare subsidy, tuition assistance, college coaching, short- and long-term disability, voluntary AD&amp;D coverage, voluntary accident coverage, voluntary life insurance, voluntary disability insurance, and voluntary long-term care insurance. We don't stop there - eligible employees can also receive mobile service &amp; home internet discounts, pet insurance, and access to commuter and transit programs! To learn about T-Mobile&rsquo;s amazing benefits, check out <i>www.t-mobilebenefits.com</i><i>.</i></p><p></p><p>
Never stop growing!<br>
As part of the T-Mobile team, you know the Un-carrier doesn&rsquo;t have a corporate ladder&ndash;it&rsquo;s more like a jungle gym of possibilities! We love helping our employees grow in their careers, because it&rsquo;s that shared drive to aim high that drives our business and our culture forward. By applying for this career opportunity, you&rsquo;re living our values while investing in your career growth&ndash;and we applaud it. You&rsquo;re unstoppable!<br>
<br>
T-Mobile USA, Inc. is an Equal Opportunity Employer. All decisions concerning the employment relationship will be made without regard to age, race, ethnicity, color, religion, creed, sex, sexual orientation, gender identity or expression, national origin, religious affiliation, marital status, citizenship status, veteran status, the presence of any physical or mental disability, or any other status or characteristic protected by federal, state, or local law. Discrimination, retaliation or harassment based upon any of these factors is wholly inconsistent with how we do business and will not be tolerated.<br>
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Talent comes in all forms at the Un-carrier. If you are an individual with a disability and need reasonable accommodation at any point in the application or interview process, please let us know by emailing ApplicantAccommodation@t-mobile.com or calling 1-844-873-9500. Please note, this contact channel is not a means to apply for or inquire about a position and we are unable to respond to non-accommodation related requests.</p></div>

Senior Applied Scientist

JPMorganChase

<div><b>JOB DESCRIPTION</b><br>
<br>
<br>
<p>Our Consumer &amp; Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions &ndash; all while ranking first in customer satisfaction. In this role, you'll apply strong technical judgment to choose the right approaches (including modern <b>LLM-based</b> methods where appropriate), evaluate performance with rigorous metrics, and ensure solutions are <b>reliable, secure, and scalable</b> in real-world environments. You'll also contribute to improving data quality and feedback loops, monitoring models in production, and continuously iterating to reduce agent effort, shorten resolution times, and increase consistency and quality across operational workflows.</p>
<p>As an <b>Applied AI/ML Vice President</b> in our <b>AI for Operations</b> organization, you will help design, build, and scale <b>cutting-edge Natural Language Processing (NLP)</b> solutions that improve experiences for both <b>customers</b> and <b>internal agents</b> supporting the bank's day-to-day operations. You'll work hands-on across the end-to-end model lifecycle&mdash;partnering with product, engineering, operations, and risk stakeholders to translate real operational needs into production-grade language capabilities such as intelligent search, summarization, classification, and next-best-action recommendations.</p>
<p><b>Job Responsibilities:</b></p>
<ul><li>Oversee the analysis of complex datasets to inform decisions on real-world applications.</li><li>Lead the development and implementation of models and algorithms to enhance existing systems, processes, and products.
</li><li>Supervise data analysis activities and ensure effective visualizations are provided.</li><li>Ensure the writing and deployment of software code in production systems is efficient and meets standards.</li><li>Anticipate risks associated with machine learning solutions and prediction/classification systems and strategize mitigation.
</li><li>Communicate complex issues clearly and credibly to senior management and stakeholders.
</li><li>Foster a transparent cross-functional work environment and influence peers and team members to uphold these standards.</li></ul>
<div><b>Required qualifications, capabilities and skills:</b><br>
<ul><li>Master's degree in computer Science, Machine Learning, or a related field with 4+ years experience OR Ph.D in computer Science, Machine Learning, or a related field with 2+ year of experience.
</li><li>Expertise in one or more of the following areas: machine learning, Graph learning, recommendation systems, network analysis, natural language processing, Reinforcement learning, MLOps, Gen AI, LLMs.
</li><li>Solid understanding of core CS concepts, including common data structures and algorithms.</li></ul></div>
<div><b>Preferred qualifications, capabilities and skills:</b><br>
<ul><li>Experienced in conducting design and code reviews.</li><li>Proficient in cloud environments such as AWS, GCP, or Azure.</li><li>Experienced in managing and deriving insights from large, both unstructured and structured datasets.</li></ul></div><br>
<p></p><p><br>
&ldquo;This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorganChase's review of criminal conviction history, including pretrial diversions or program entries.&rdquo;</p>
<b>ABOUT US</b><br>
<br>
<br>
<p>Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
</p><p></p><p>We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
</p><p></p><p>We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.</p>
<p></p><p>Equal Opportunity Employer/Disability/Veterans</p><br>
<br>
<br>
<b>ABOUT THE TEAM</b>
<br>
<br>
Our Consumer &amp; Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions &ndash; all while ranking first in customer satisfaction.</div>

Applied AI ML-Vice President

Traba

<div><p>Traba is the AI operating layer for the industrial supply chain.</p><div></div><p><br>
We started in workforce&mdash;temp staffing, the biggest operational pain point for the manufacturing and logistics customers we serve&mdash;and used it to embed ourselves inside their daily operations and create a far better customer experience through technology.</p><div></div><p><br>
Now those same customers are pulling us beyond staffing into the broader operational workflows that run their facilities. That foundation gave us proprietary data from millions of shifts and deep enterprise relationships.</p><div></div><p><br>
But our edge is more than data: by connecting to the systems running across every facility and activating the workers already on our platform to execute against them, we are building applied AI that drives real productivity gains and transforms how the global supply chain operates at scale.<br>
<br>
We are backed by Founders Fund, Khosla Ventures, and General Catalyst.</p><div></div><p><b><br>
You'll build the AI agents themselves&mdash;the harnesses, evals, orchestration, and model strategy the rest of Traba's product runs on.</b> We're seeking an entrepreneurial AI Agent Engineer to join as a founding member of the Agents team and build the next layer of Traba's product&mdash;an agentic platform that synthesizes the data flowing through our marketplace and operates autonomously inside our customers' supply chain workflows. (Our Applied AI team puts these agents to work across the product; you own the agents and infrastructure they depend on.) You'll embed deeply in our customers' operations, design and ship production agent harnesses on top of frontier models, and turn what you learn in the field into durable product. You will partner closely with our CTO, product, and our operators to take 0-to-1 ideas to scaled deployments.</p><div><br>
</div><h2 class="jobSectionHeader"><b>
About You</b></h2><ul><li><p><b>
Builder with an AI operator's instinct.</b> You've shipped real product on top of LLMs&mdash;not just chat wrappers. You've designed agent harnesses, structured tools, written evals, and tuned prompts against production traces. You think in capability, reliability, and unit economics&mdash;not just whether the model says the right thing.</p></li><li><p><b>
Domain-immersed.</b> You enjoy time with the people who do the work&mdash;learning an industry's vocabulary, edge cases, and operational tempo&mdash;and let that shape what you build.</p></li><li><p><b>
High-agency in ambiguity.</b> Dropped into a fuzzy customer problem with a half-formed hypothesis and a deadline, you scope, build, evaluate, and ship without waiting for a spec.</p></li><li><p><b>
Sweat both ends of the stack.</b> You move between prompt iteration, eval design, backend services, and customer-facing UI in the same week, and you care about evals that catch regressions and traces that are easy to debug.</p></li></ul><div></div><div><br>
</div><h2 class="jobSectionHeader"><b>
You Will</b></h2><ul><li><p>
Embed with customers and operators to understand how supply chains run today&mdash;then design and ship agents that take meaningful work off their plate.</p></li><li><p>
Build production agent systems on frontier LLMs: tool use, sub-agents, retrieval, structured outputs, MCP servers, and the orchestration that ties them together.</p></li><li><p>
Own evaluation as a first-class discipline&mdash;datasets from real traces, rubrics and graders, experiments, and improvements you can prove move the needle.</p></li><li><p>
Architect the data, services, and APIs the agent layer depends on&mdash;integrating our internal systems with customers' WMS, TMS, and ERP environments.</p></li><li><p>
Codify repeatable deployment patterns so each new customer rollout is faster than the last.</p></li></ul><div></div><div><br>
</div><h2 class="jobSectionHeader"><b>
You Have</b></h2><ul><li><p>
1+ years of software engineering experience, with a track record of shipping LLM- or agent-based features to production.</p></li><li><p>
Strong in Python and/or TypeScript/Node.js, and comfortable designing APIs, distributed systems, and data models in PostgreSQL.</p></li><li><p>
Hands-on with the modern agent stack: production-scale prompt engineering, evaluation frameworks, orchestration patterns, and frontier model APIs.</p></li><li><p>
A track record of building in fast, ambiguous environments&mdash;ideally at a vertical AI, AI-agent, forward-deployed, or data-product company.</p></li><li><p>
Excellent written and verbal communication&mdash;you can run a customer workshop in the morning and write a clean design doc in the afternoon.</p></li></ul><div></div><div><br>
</div><h2 class="jobSectionHeader"><b>
Benefits</b></h2><ul><li><p>
Start-up equity</p></li><li><p>
Competitive Salary</p></li><li><p>
100% Paid health, dental &amp; vision coverage</p></li><li><p>
Dinner Provided via DoorDash, free DashPass &amp; stocked kitchen for NY employees</p></li><li><p>
Commuter benefit</p></li><li><p>
Gympass Benefit</p></li><li><p>
✚✚ Additional: One Medical Membership, Gympass, HSA via Optum, Talkspace, HealthAdvocate, Teledoc Health</p></li></ul><div><br>
</div><h2 class="jobSectionHeader"><b>
Salary Range Details</b></h2><p>
The compensation range for this position is set between $140,000 and $200,000, reflecting our market analysis and other relevant considerations. However, exceptions may be made for candidates with qualifications that significantly differ from those outlined in the job description.</p><div><br>
</div><h2 class="jobSectionHeader"><b>
Equal Opportunity Employer</b></h2><p>
Traba is dedicated to promoting Equal Opportunity employment practices. We evaluate all applicants without discrimination based on race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other characteristics that are legally protected by local, state, or federal regulations. We encourage applicants from a variety of backgrounds, experiences, and skill sets.</p><div><br>
</div><h2 class="jobSectionHeader"><b>
Our Values</b></h2><p><b>
Dream Big -</b> We are on a path to change the world for the better. We create and communicate a bold direction that inspires a life-changing vision. We don&rsquo;t sacrifice long-term value for short-term results.</p><p><b>
Olympian&rsquo;s Work Ethic -</b> Changing the world never comes easy. We work harder, longer, and smarter, not just two out of three. We put everything we have on the field.</p><p><b>
Growth Mindset -</b> We confront the toughest challenges head-on and persevere. Sometimes we fail, but we brush ourselves off, adapt, learn, and push forward with resilience.</p><p><b>
Customer Obsession -</b> We go the extra mile for our workers and businesses. We remain focused on delivering high-quality products and services that solve this massive and overlooked industries&rsquo; problems</p><div></div><p><br>
Job Applicant Privacy Notice</p><p>
Compensation Range: $140K - $200K</p></div>

Software Engineer (AI Agents)

Giga

<div>
 <strong>
  About Giga
  <br/>
  <br/>
 </strong>
 Giga has recently raised a $61M Series A and has several paying customers, including DoorDash. We&rsquo;re building the next generation of customer experience &mdash; real-time AI agents that can understand emotion, resolve issues instantly, and scale across the world&rsquo;s largest enterprises.
 <br/>
 <br/>
 It&rsquo;s an exciting inflection point for the company. While we have been successful, we have larger ambitions. Our goal is to become the go-to AI platform for all enterprise automation, powered by our voice superintelligence. To achieve this, we need more great engineers.
 <br/>
 <br/>
 The work affects millions of people every day and our engineers have autonomy and make true impact. This opportunity is unique because we have brilliant founders, have found commercial success, and see a clear path to becoming a generational company. Some further info about us:
 <br/>
 <br/>
 <ul>
  <li>
   Voice AI startup Giga raises $61M Series A
  </li>
  <li>
   DoorDash and Giga Partnership
   <br/>
   <br/>
  </li>
 </ul>
 Giga builds AI agents trusted by the largest B2C companies in the world. Industry leaders like DoorDash trust Giga with their most complex support and operations workflows across voice, chat, and email. If being a part of this resonates with you, please apply!
 <br/>
 <br/>
 <strong>
  The Role
  <br/>
  <br/>
 </strong>
 We're looking for software engineers to help build the systems that power our AI agents. You'll work across the backend, from data pipelines and integrations to agent infrastructure, shipping features alongside experienced engineers who will help you grow.
 <br/>
 <br/>
 This is a role where you'll contribute to real problems from day one. We expect you to ramp up quickly, take ownership of your work, and operate with increasing independence as you learn the codebase.
 <br/>
 <br/>
 <strong>
  What You'll Work On
  <br/>
  <br/>
 </strong>
 You'll contribute to projects across our stack. Some examples:
 <br/>
 <br/>
 <ul>
  <li>
   Atlas: Building features for our AI assistant: charts and alerts in Slack, natural language queries, and expanding Atlas to manage platform resources
  </li>
  <li>
   Activity Stream: Log visualization with filters, timestamps, and frequency charts to give visibility into agent behavior
  </li>
  <li>
   Dynamic knowledge: Adding time-based knowledge (like ongoing incidents) that auto-updates from sources like status pages
  </li>
  <li>
   Agent memory: Conversation awareness and recent interaction lookups so agents remember context across sessions
   <br/>
   <br/>
  </li>
 </ul>
 As an early-career engineer, you'll be paired with senior engineers on larger initiatives while also owning smaller projects end-to-end as you ramp up.
 <br/>
 <br/>
 <strong>
  You Might Be a Fit If You
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Have 1-3 years of professional software engineering experience
  </li>
  <li>
   Are curious and ask good questions&mdash;you want to understand why things work, not just how
  </li>
  <li>
   Can take feedback well and iterate quickly
  </li>
  <li>
   Prefer shipping over perfection but still care about quality
  </li>
  <li>
   Want to grow at a startup where you'll have real responsibility early
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Perks &amp; Benefits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Competitive base + bonus + equity
  </li>
  <li>
   Catered lunch daily
  </li>
  <li>
   Dinner stipend
  </li>
  <li>
   $500/month wellness &amp; commuter benefit (gym, fitness classes, mental health)
  </li>
  <li>
   401(k) plan
  </li>
  <li>
   Medical, dental, and vision coverage
   <br/>
   <br/>
  </li>
 </ul>
 Giga is an equal opportunity employer. We're committed to providing equal employment opportunities regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law.
 <br/>
 <br/>
 Compensation Range: $160K - $250K
 <br/>
 <br/>
</div>


Software Engineer I / II

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