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* Develop, maintain and tailor training programs covering remote sensing principles, SAR fundamentals, and the practical application of ICEYE’s technology across operational use cases. * Align training content with evolving product features and customer needs, ensuring materials reflect the latest advancements in ICEYE’s portfolio of offerings.

Transforms .NET developers and graduates into techno-functional consultants through structured, practical learning. .NET Developers.

Aleph Alpha is looking for Senior AI Researchers to develop and evaluate post-training methods that reduce LLM hallucinations and improve reliability.

Location: United States; Canada Workplace: OnSite WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview As a Member of Technical Staff in Post-Training Data Infrastructure, you will build and own the pipelines that produce the post-training data for our large language models (LLMs), from SFT and RL data to synthetic and human-annotated data. You will work closely with researchers and annotation teams so they can iterate on data as quickly as they iterate on models. Key Responsibilities - Build and maintain data pipelines for SFT, preference, and RL post-training data. - Own dataset quality, versioning, and reproducibility. - Turn research data recipes into production-grade, reusable components. - Scale model inference for data generation and model-based grading. - Design data formats and schemas that keep post-training datasets consistent and efficient to train on. - Collaborate with researchers and engineers to make sure data pipelines keep pace with the needs of cutting-edge language models. Qualifications - Strong software engineering skills. - Experience designing and building large-scale data pipelines for machine learning, ideally for LLM post-training. - Track record of running distributed data processing and model inference at scale. - Good understanding of post-training methods (e.g., SFT, RLHF, DPO) and how data shapes model behaviour. - Excellent communication skills. This is neither an exhaustive nor necessary set of attributes. Even if none of these apply to you, but you believe you will contribute to Cohere, please reach out. We value diverse backgrounds and perspectives at Cohere   FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: Europe; New York; Toronto Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Key Overview: As a Member of Technical Staff in Post-Training, you will train our large language models (LLMs) with reinforcement learning and develop methods that help them generalize beyond the distribution they were trained on. You will design the training recipes, environments, and evaluations that tell us whether a model has truly learned a skill or has only fitted its training tasks, and turn what works into the recipes behind our production models. You will work closely with the post-training data infrastructure, evaluation, and pre-training teams. Key Responsibilities - Design, run, and analyse large-scale RL post-training experiments (e.g., RLHF, RL from verifiable rewards). - Research and develop methods that improve out-of-distribution generalization, such as reward design, environment and task diversity, curricula, and regularization. - Build held-out evaluations that measure generalization to unseen tasks, domains, and formats, and that catch reward hacking and benchmark overfitting. - Diagnose training dynamics and failure modes, including instability, reward over-optimization, and capability regressions. - Turn successful research into robust, reproducible training recipes for production models. Qualifications - Strong research and software engineering skills, with hands-on experience training LLMs. - Experience applying reinforcement learning to LLMs (e.g., PPO, GRPO, RLHF, RLVR), ideally at scale. - Track record of work on generalization, robustness, or distribution shift, through publications or shipped models. - Rigorous experimental practice: clean ablations, careful controls, and sound conclusions from noisy results. - Experience with distributed training (e.g., JAX, PyTorch, FSDP, Megatron) is a plus. - Excellent communication skills. - Deep understanding of data quality principles and best practices: demonstrates willingness to dive deep into data while possessing strong intuition for assessing the quality of datasets and anticipating how different data characteristics will impact model training outcomes. Working Location This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role.   FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: San Francisco Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE This role sits at the applied end of our post-training research efforts. You will work directly with stakeholders from the world’s fastest-growing AI companies to post-train open-source models that outperform frontier closed models on their specialised tasks. Your day-to-day is finding creative ways to extract signal from complex, domain-specific datasets and building the reward functions, environments, eval harnesses, and training pipelines that turn that signal into better models. The models you train ship to production and reach millions of users. We are looking for people with hands-on LLM fine-tuning and RL experience. Researchers who are excited by the prospect of shipping models into production, who can translate a customer's domain-specific requirements into an effective training curriculum, and who know when to be rigorous and when to iterate fast. RECENT RESEARCH - Dense, on-policy or both? https://www.baseten.co/research/dense-on-policy-or-both/ - Repeated kv cache for long-running agents https://www.baseten.co/research/repeated-kv-cache-for-long-running-agents/ - Distillation without the dark – replicating black-box on-policy distillation on Baseten https://www.baseten.co/research/distillation-without-the-dark/ RESPONSIBILITIES - Design and run post-training pipelines: SFT, GRPO, DPO, RLVR, reward function engineering, and synthetic data generation. - Build task-specific training environments and evals tailored to customer domains like healthcare, code generation, and legal, spanning multi-turn tool use, sandboxed execution, and agentic workflows. - Work directly with customers to translate production data into training signal, designing reward loops from real usage patterns and handling distribution shift. - Run and analyze training experiments end-to-end: diagnose reward hacking, importance sampling drift, and advantage estimation instabilities. - Publish findings at top venues and contribute to Baseten's open-source training libraries. QUALIFICATIONS - Hands-on experience training LLMs with reinforcement learning — demonstrated understanding of GRPO or PPO beyond recipe-level reproduction, including group advantage computation, clipped objectives, and KL penalty design - Strong intuition for reward engineering: the ability to distinguish between a reward that trains effectively and one that will exploit at scale - Experience building multi-turn agent environments with tool use, not limited to single-turn question-answering setups - Comfort working across the full pipeline from dataset construction through training, evaluation, and deployment - Experience with production ML systems. Preference for candidates who have closed a training–inference loop where production data feeds back into model improvement PREFERRED QUALIFICATIONS - Experience with RL training frameworks - Publications at NeurIPS, ICML, ICLR, focused on RL for LLMs, reward modeling, or alignment BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: San Francisco; Remote; New York Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re looking for a high-performing strategic finance professional to join our growing Product Finance team. Training is one of Baseten's fastest-evolving businesses and it won't be the last new product line we launch. You'll own the economics of Training end to end and be the finance owner for new products as they go from idea to launch to scale, partnering directly with Product, Engineering, Infrastructure, and GTM leadership on the pricing, margin, and capacity decisions that shape each business. This is a builder role: much of what you'll own doesn't exist yet as a model, a dashboard, or a process. This role is ideal for someone with 5 to 8 years of experience across strategic finance, investing, and/or investment banking who wants broad exposure to company-building inside a fast-scaling AI infrastructure company. Experience at a usage-based company is a plus. RESPONSIBILITIES - Build and maintain cost-to-serve models for Training engagements across compute, delivery time, and reserved capacity - Own Training pricing and recommend structures across committed engagements, usage-based pricing, and packaged offerings - Track training capacity utilization and tie capacity plans to pipeline - Run the monthly Training business review across bookings, utilization, margin, pipeline, and renewal and expansion trends - Own the Training forecast and annual plan, including compute needs, unit costs, and multi-year P&L - Partner with Product on new products from concept onward, building pre-launch business cases, cost-to-serve views, and go/no-go recommendations - Set launch pricing and packaging for new products - Define success metrics and scale criteria at launch REQUIREMENTS - Bachelor's degree in Business Administration, Finance, or Economics - 5+ years of experience in strategic finance at a high-growth company, PE/VC investing, and/or investment banking - Excellent financial modeling and analytical skills, including building unit economics or cost-to-serve models from raw usage and cost data - Ability to synthesize complex information into clear recommendations for executives - Comfortable building from scratch and making decisions with incomplete data in a fast-moving environment - Strong attention to detail with a bias toward ownership and execution - Excellent communication and presentation skills - High intellectual curiosity and interest in AI / infrastructure / developer tooling - Advanced Excel / Google Sheets skills; familiarity with SQL or BI tools is a plus NICE TO HAVE - Experience with GPU compute economics or cloud infrastructure - Familiarity with how ML model training and fine-tuning work - Experience with product-led growth economics, such as free tiers, credits, and conversion - Experience pricing or launching a new product line BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

About the Client Our client is involved in an innovative data-collection project, which focuses on creating video datasets for training AI models. These AI models are designed to learn from first-person (POV) video footage. The captured videos depict real people involved in hands-on tasks with a mounted phone on their head or chest, paired with spoken narration. The purpose is to enable the model to connect visual inputs (objects, hands, actions) with audio descriptions. About the Role The Recorder role requires individuals who can master a specific hands-on activity from a selection of verticals. You will need to film yourself performing these tasks from a first-person perspective using your smartphone while ensuring the tasks are clearly visible. If fluent in English, you may narrate live; otherwise, ambient audio will suffice, and a separate narrator will cover the task later. Tasks & Deliverables — Select a mastered sub-area activity and record a complete end-to-end process. — Ensure hands and the procedure are constantly in focus. — Provide live narration if fluent in English or ambient audio for post-recording narration. — Deliver videos in MP4 format with accompanying JSON metadata. — Maintain narration density at 25 words per minute; ensure 90%+ of speech describes the setting or task steps. Required Skills — Mastery of at least one specific sub-area activity from the provided list (e.g., cleaning, laundry, organizing, pet care, repairs, gardening, sewing, woodworking, automotive repair, art, technology use, personal care, medical procedures, culinary skills, lab protocols). — Capability to record stable, clear POV videos with a smartphone. — Ability to work in a real setting without third parties in frame. — Competent in following a prepare → execute → finish script for filming tasks. Nice-to-have Skills — Experience recording tutorials or classes. — Access to various settings for diverse video backgrounds. — Owns equipment like a head/chest mount, image stabilization tools, or a good microphone. Rules — No personal data on video — no third-party faces, screens, documents, plates, addresses, mirror reflections. — 100% human narration — no TTS or synthetic voice. Engagement Details — Compensation model: Hourly paid, considering the total number of hours for approved videos. — Commitment Type: Flexible hours based on video submissions. — Duration: Ongoing, with earnings based on the number of approved videos. — Location: Remote, with flexible overlap with client's timezone. — Start Date: Immediate start upon approval of test video.

About the Client: Our client is involved in an innovative data-collection project, which focuses on creating video datasets for training AI models. These AI models are designed to learn from first-person (POV) video footage. The captured videos depict real people involved in hands-on tasks with a mounted phone on their head or chest, paired with spoken narration. The purpose is to enable the model to connect visual inputs (objects, hands, actions) with audio descriptions. Sub-areas for the videos include: Home & Daily Tasks: cleaning, laundry (sorting, folding), organizing a closet, house tours, pet care, packing luggage, loading appliances / dishwashing. Repairs & DIY: home repair, gardening / farming, furniture assembly, woodworking, plumbing, electrical work, bicycle maintenance, soldering electronics. Textile & Craft Arts: sewing, knitting, crocheting, using a loom, leathercrafting, bookbinding, crafting jewelry, pottery / ceramics. Professional Trades & Industrial: automotive repair / maintenance, warehousing / logistics, construction / woodworking, laboratory work, operating heavy machinery controls, assembly-line packaging. Hobbies & Arts: art – drawing, ceramics, painting, playing instruments, model building, outdoor survival / camping, calligraphy. Technology & Computing: using computers or devices (e.g. audio mixers), gaming, product demos, VR / AR interaction, 3D printer setup / maintenance. Outdoors & Activity: city tours, shopping, navigating public transit. Personal Care: haircut, applying makeup, detailed grooming routines. Specialized & Professional: medical procedures, first aid training, professional barista workflows, culinary chef / knife work, lab protocols (pipetting, titrations). About the Role - Narrator: Watches the POV video and describes the scene and task in first person, in English, as if explaining it to a model that can't see. Fluency and describing ability matter most; knowing the activity is not required. Deliverable: — audio narration synced to the video, recorded after the footage. Language: — English; fluency is criterion #1. Density: — at least 25 words/min on average, no long silences. Content: — 90%+ about the setting or task steps. Required Skills: — English fluency. — Ability to narrate pre-recorded videos. — All details on the Acceptance Criteria will be shared prior to the work. Rules: — No personal data on video — third-party faces, screens, documents, plates, addresses, mirror reflections. — 100% human narration — no TTS or synthetic voice. Engagement Details: Compensation model: Hourly paid, considering the total number of hours for approved videos. Commitment Type: Flexible hours based on video submissions. Duration: Ongoing, with earnings based on the number of approved videos. Location: Remote, with flexible overlap with client's timezone. Start Date: Immediate start upon approval of test video.

Location: Tbilisi, Georgia About Wolt At Wolt, we create technology that brings joy, simplicity and earnings to the neighborhoods of the world. In 2014 we started with delivery of restaurant food. Now we’re building the delivery of (almost) everything and you’ll find us in over 500 cities in 30 countries around the world. In 2022 we joined forces with DoorDash and together we keep on dreaming big and expanding across the globe. Working at Wolt isn’t always easy, but it’s definitely exciting. Here you’ll learn more, build more, and ship more than in most other companies. You’ll be challenged a lot, but also have a lot of fun on the way. So, if you’re a self-starter with drive and entrepreneurial spirit, this could be the ride of your life. As an SSC Training Manager, you will oversee the training efforts within our Shared Service Centre Team, ensuring that all training programs are aligned with global standards while addressing local needs. You will manage the SSC Training Team, track KPIs, and ensure the successful rollout of global learning initiatives. If you are eager to make a difference in how teams are trained and onboarded, this role is perfect for you. Essential Duties and Responsibilities Team Management: Manage and lead Training Leads and Training Specialists to ensure effective execution of training programs. Oversee the development and performance of the Training Team, ensuring all trainers are equipped to meet local and global objectives. KPI Tracking and Development: Track and report on the relevant Training KPIs to ensure the effectiveness of training programs and drive continuous improvement. Analyze training performance data to identify areas for enhancement and drive strategic changes based on those insights. Train-the-Trainer Certification: Implement and track the Train-the-Trainer certification process, ensuring trainers are prepared to deliver high-quality learning experiences. Ensure trainers are certified and maintain ongoing competency through continuous evaluation. Learning Strategy Development: Manage high-volume, cohort-based onboarding programs that deliver consistent agent readiness across the SSC. Continuously refine the program to accelerate ramp-up without compromising quality. Develop instructional learning strategies tailored to the needs of SSC, focusing on both onboarding and continuous learning. Collaborate with global teams to define and validate new training approaches that enhance learning effectiveness. Project and Initiative Rollouts: Lead the rollout of global training projects and initiatives, ensuring that the SSC team is aligned with global standards. Coordinate with local teams to implement global changes and customize the delivery of these initiatives to suit local nuances. Global-Local Collaboration: Serve as the key liaison between local teams and the global training organization, ensuring that local feedback and requests are communicated and considered in global decision-making. Partner with cross functional teams to identify performance trends and prioritize improvement efforts across the SSC agent population. Act as SCC’s primary voice in global training design and delivery, surfacing local performance patterns, flagging content gaps and co-developing learning solutions with the global training team. Our humble expectations Leadership and Team Development: Proven ability to lead and inspire a training team, setting a strong example and guiding team members to deliver impactful learning experiences. Committed to fostering a culture of growth, ensuring team members have the support and resources needed to excel. Data-Driven Decision Making: Skilled in interpreting data to measure training effectiveness and  translate insights into learning program adjustments. Instructional Design: Knowledgeable in creating tailored learning strategies that balance local needs with global goals, particularly for onboarding and continuous learning. Project Management: Strong project coordination skills, especially in managing training rollouts and adapting them to fit local requirements. Performance Consulting: Able to work with cross functional partners to diagnose the root cause of performance gaps and design the appropriate, targeted learning interventions. Clear Communicator: Able to bridge global and local teams effectively, communicating needs and updates in a clear, actionable way. Adaptable & Culturally Aware: Flexible in approach, with a sensitivity to cultural differences and local needs, ensuring training programs are relevant. Problem Solver with a Strategic Lens: Quick to identify challenges and implement improvements, especially when adapting global programs to local nuances. Attention to Detail: Meticulous in ensuring that training content and delivery meet both global standards and local expectations. Accountability for SSC Success: Deep commitment to the growth and wellbeing of the SSC Team, taking ownership of training outcomes, ensuring alignment with organizational standards and addressing performance gaps. Languages : Fluent English is required. Location : Available to work from our Tbilisi office. Next steps If you are excited about working in a high-growth environment, taking ownership and being part of an extremely ambitious team, then click below to apply and get the conversation going! We will be reviewing applications on an ongoing basis, so if this sounds like an opportunity you want to pursue, apply today! Please submit your up-to-date resume in English. Our Commitment to Diversity and Inclusion We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel. Beware of recruitment scams: DoorDash, Deliveroo, and Wolt will never ask you to pay money or share sensitive financial information during hiring — learn more about our legitimate recruiting process at Recruitment Scam Awareness - DoorDash .

Location: San Francisco; New York Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE Forward Deployed Engineers work directly with the largest and fastest-growing AI companies in the world, owning their technical outcomes on Baseten and taking on the hardest problems in serving and improving models at scale. The work spans the model lifecycle: inference, post-training, and the systems that tighten the loop between them. - Act as each account's de facto CTO on Baseten, with final accountability for how their workloads are designed, run, and scaled. - Take customer objectives from vague to shipped: frame the problem, define the spec and success criteria, build the PoC, and carry it through to production quickly, using the right tools for the problem. - Design the evals and benchmarks that isolate where quality or performance falls short, then close the gap yourself, whether that means optimizing inference, improving the model through post-training, or reworking the eval itself. - Be the first responder to mission-critical failures including triage, owning the fix directly or route to the owning team and stay accountable until it ships. - Build internal systems so that each engagement is faster than the last. This includes tooling and automation for eval and deployment infrastructure, and the recipes and reference implementations that make the product more self-serve. - Shape the product itself, channeling what your accounts need into the roadmap and shipping fixes and features into Baseten's codebase yourself. - Do all of this across multiple accounts at once, sequencing the work, pulling in the right people at the right time, and keeping customers and internal stakeholders aligned on status and risk. REQUIREMENTS - Minimum 1-2 years of software engineering experience, shipping and maintaining code in large production systems, ideally with breadth across the stack - Experience debugging complex production issues - working through logs, metrics, and traces to root-cause problems in unfamiliar systems - Confidence owning ambiguous technical problems. This includes triaging, making decisions under uncertainty, and knowing when to pull in other engineers who own the underlying systems - Motivation beyond pure engineering. An interest in wanting to work directly with customers, understand their problems firsthand, and influence the product - Clear communication on complex technical topics, whether you're talking to a customer's engineers or their leadership - Genuine curiosity about AI inference and training, and a drive to become an expert in the infrastructure powering it - Willingness to respond to customers outside regular working hours and participate in an on-call rotation - Excitement about solving problems for some of the largest and fastest-growing companies in the world running mission-critical AI workloads WHAT YOU'LL BRING We don't expect any one person to cover all of this - the strongest candidates may spike in one or two of the following: - Depth in a core infrastructure domain such as storage systems or networking (anywhere from the cloud layer to cluster interconnects like InfiniBand and RoCE) - Experience operating distributed compute platforms like Kubernetes, Slurm, or Ray, especially for GPU workloads - A detailed understanding of LLM architectures and modern inference engines like vLLM, TensorRT-LLM, or SGLang - The ability to profile and optimize GPU workloads, in training or serving - Hands-on experience with post-training techniques like SFT and RL, or a broader deep learning background plus fluency in a tensor computation library like PyTorch or JAX - Operational depth - running on-call, leading incident response, debugging distributed systems under pressure BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: Tokyo, Japan Workplace: Hybrid WHO WE ARE Notion is the collaborative AI workspace where teams and agents think together https://www.youtube.com/watch?v=vkpYpWfEK5s. We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. ABOUT THE ROLE We’re looking for an experienced Localization Project Manager — Japan Training Quality to support localization for Customer Education, helping ensure Notion training content feels accurate, clear, culturally relevant, and ready to use for learners across the globe. You’ll work at the intersection of localization quality, training implementation, and program management, collaborating with Localization, Partner Enablement, Customer Education, vendors, and language specialists. You’ll help turn translation feedback, learner experience issues, and regional quality needs into practical improvements across training content, quizzes, LMS setup, and repeatable localization workflows. The ideal candidate combines native-level Japanese language expertise with a deep understanding of what effective education looks like in the Japanese market. WHAT YOU'LL ACHIEVE - Own and apply Japanese localization QA standards across training content, including checking for accuracy, clarity, tone, terminology, and cultural nuance - Support development of glossaries, style guides, QA checklists, review processes, and localization assets - Become a go-to partner for translation questions related to Notion-specific concepts, product terminology, and training context - Support QA of technical implementation in eLearning authoring tools and LMS environments (course files, quizzes, answer selections) - Coordinate across Customer Education, Partner Enablement, Localization, and vendors to align on priorities, timelines, translation progress, and quality expectations - Identify workflow risks and recommend improvements that improve translation quality and reduce time-to-launch - Document repeatable processes that make training and help center localization easier to manage over time SKILLS YOU'LL NEED TO BRING - Strong understanding of localization workflows, including vendor collaboration, review cycles, glossaries, style guides, QA rubrics, and linguistic QA - Experience with Japanese localization QA, ideally for SaaS, technical training, customer education, or partner enablement content - Ability to review translated content for quality, clarity, terminology accuracy, cultural nuance, and learner comprehension - Familiarity with eLearning or LMS tools; experience with platforms like Skilljar or Parta authoring tools is a plus - Comfort working with technical or product-specific terminology that may not translate directly - Strong attention to detail, especially in learner-facing content, quizzes, course setup, formatting, and implementation QA - Strong project management skills and ability to bring structure into ambiguous areas WHY THIS ROLE MATTERS We want all of our learners should feel like Notion training content was made for them — not simply translated for them. High-quality localization has a direct impact on learner trust, comprehension, launch readiness, and regional enablement outcomes. This role will help Customer Education and Partner Enablement move faster while raising the quality bar: reducing rework, catching issues before launch, improving vendor feedback loops, and creating a clearer, more repeatable operating model for training localization This is a 6-month, part-time role with option to extend. Preferred location is Tokyo, but we're open to remote applicants with strong Japanese market expertise and timezone overlap with Japan and Notion's International Experience team. Availability: 20 hours/week #LI-Onsite A NOTE ON AI You don’t need deep AI expertise for every role, but we do expect every Notino to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement — when that’s the case, we'll say so explicitly in the qualifications. People who thrive here don’t treat AI as a novelty. They use it to think better, and make their work easier for others to build on. EQUAL OPPORTUNITY & ACCOMMODATIONS We hire talented people from a wide range of backgrounds. If you’re excited about this role but don’t meet every bullet, we still encourage you to apply. Notion is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. Consistent with applicable law, we will consider for employment qualified applicants with arrest and conviction records. Notion provides reasonable accommodations during the application process; if you need one, please let your recruiter know. Notion is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Notion considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Notion is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please let your recruiter know.

Location: San Francisco; New York Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re looking for a product marketer to own positioning, launches, and customer stories for Baseten’s post-training offerings. You’ll work closely with researchers, engineers, and customers to understand a fast-moving market and give MLEs and researchers a clear reason to choose Baseten Training. You’re an excellent writer, a curious researcher, and a fast learner who can develop a strong point of view on technical topics, rather than just translating product features into content. Prior post-training experience is helpful, but not required. There’s no single path into this role. We welcome candidates from non-traditional backgrounds who have built strong writing, market judgment, and strategic thinking plus execution skills, whether that comes from product marketing or another field. We care more about the quality of your work and how quickly you learn than a particular title or industry background. If you’re passionate about AI infrastructure, post-training, developer engagement, and simplifying complex technologies for real-world adoption, we want to hear from you. RESPONSIBILITIES - Positioning & Messaging: Develop clear and differentiated messaging that articulates the value of Baseten’s Training platform to developers and enterprise customers. - Competitive Insights: Understand the fast-moving AI market and build competitive and market analysis to inform product positioning strategies. - Narrative Development: Shape how the market thinks about closed-to-open weights models and post-training ROI. - Product Storytelling: Own the launch process for new features and products, collaborating closely with product, engineering, sales, and growth teams. - Customer Stories: Work with our customers to understand the technical differentiation, key story, and compelling customer results. Then own telling the story from customer interviews through distribution and publication. REQUIREMENTS - Experience owning positioning, launches, or customer storytelling, gained through product marketing or related work. - An interest in AI infra and post-training with a proven aptitude to learn quickly. - Excellent writing: You can turn complex product capabilities into clear, accurate, compelling narratives. We’d love to see some of your work. - Fast learning: You get up to speed on unfamiliar technical concepts, ask thoughtful questions, and work with engineers and researchers to get the details right. You can operate at the right technical altitude when talking to different stakeholders. - Competitive judgment: You proactively research customer alternatives and develop a clear point of view on differentiation. - Hands-on ownership: You prioritize in ambiguity, navigate cross-functional trade-offs, and drive work through to launch. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: New York; San Francisco ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: We’re building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work. We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. WHAT YOU’LL WORK ON: - Improve existing methods and develop new techniques for large-scale model training, optimization, and inference - Extend models to long-context and long-horizon tasks - Improve inference-time efficiency, reliability, and robustness in high-stakes real-world deployments YOU MAY BE A FIT IF: - You have a PhD in computer science, machine learning, or a related field - You have a demonstrated record of research accomplishments in reinforcement learning, machine learning, foundation models, or related fields - You have experience with large-scale training and inference infrastructure, including distributed systems and multi-node GPU clusters - You’ve developed, trained, optimized, or deployed state-of-the-art large-scale models - You have first-author publications at leading venues such as NeurIPS, ICML, ICLR, CoRL, CVPR, UAI, JMLR, or TMLR - You have a mission-driven mindset and a strong desire to translate research advances into meaningful product impact - You have a collaborative spirit and can work effectively across research and engineering teams Candidates with a master’s degree and significant research or industry experience will also be considered.

Location: San Francisco Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. We are looking for an engineer with strong experience in machine learning and solid foundations in math and computer science to join our growing Post-Training team at Baseten. THE ROLE Custom models are instrumental to the success of Baseten customers. By inference volume, the overwhelming majority of traffic at Baseten is to and from models that have been post-trained in some way, whether that be through reinforcement learning, supervised finetuning, a recent technique from the literature, or an in-house research technique from Baseten. The Post-Training team is responsible for the success of our customers’ post-trained models, and we employ a wide array of techniques to produce models that are more efficient and higher quality than even the biggest closed source models for the customer’s specific needs. Your role as a research engineer is to build the in-house tooling to support all of this. We care about training a wide spectrum of different model architectures with a variety of techniques efficiently and at scale. At times this involves zooming deep into a particular technical topic, but more often it involves working across the stack as a whole - systems-level concepts like Kubernetes, cgroups, storage systems, and networking topologies, as well as PyTorch distributed tensor computation, and GPU kernels. The Manifesto: https://labs.baseten.co/manifesto RECENT RESEARCH - Dense, on-policy or both? https://www.baseten.co/research/dense-on-policy-or-both/ - Repeated kv cache for long-running agents https://www.baseten.co/research/repeated-kv-cache-for-long-running-agents/ - Distillation without the dark – replicating black-box on-policy distillation on Baseten https://www.baseten.co/research/distillation-without-the-dark/ We don’t have a rigid set of skills, but here’s some of what we’re looking for: - A deep understanding of modern ML techniques and tools for training transformers - Advanced experience in a tensor/array computation library like PyTorch, TensorFlow, Jax, or similar - A detailed understanding of transformer training parallelism strategies like data parallelism, sharded data parallelism, tensor parallelism, pipeline parallelism, context parallelism - The experience and knowledge to profile and improve the performance of a distributed GPU program in PyTorch or a similar library - The ability to perform roofline analysis on a transformer training setup - A willingness to dive into messy problems, work with researchers, derive specifications by asking important questions, and execute - Familiarity with HPC and distributed computing platforms like Slurm, Ray, Kubernetes, and Dask - Familiarity with cluster networking technology like Infiniband, RoCE, GPUDirect - Solid fundamentals in operating systems concepts like processes, files, kernel drivers, containerization, and networking protocols - A sense of creativity and willingness to ask difficult questions about our approach, assumptions, and tooling choices BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: San Francisco Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE This role sits at the frontier of our research agenda. You will pursue open problems at the intersection of post-training methodology and performant inference, and then collaborate with research engineering to translate findings into production systems. A meaningful portion of your time will be dedicated to research that deepens our understanding of how models learn, alignment, and architectural efficiency — questions that may not have immediate product application. The remainder will be directed toward research that solves concrete problems for Baseten's platform and customers, who are the fastest growing AI companies in the world like Cursor, Lovable, and Notion. We are looking for someone with sharp research taste and genuine creative instinct for problem selection. Someone who can identify questions that matter, design clean experiments to answer them, and push the state of the art. The environment here is not theoretical, but rather research that can be validated with eager customers who are serving billions of tokens a second. The Manifesto: https://labs.baseten.co/manifesto RECENT RESEARCH - Towards infinite context windows: neural KV cache compaction https://www.baseten.co/research/towards-infinite-context-windows-neural-kv-cache-compaction/ - Dense, on-policy or both? https://www.baseten.co/research/dense-on-policy-or-both/ - Repeated kv cache for long-running agents https://www.baseten.co/research/repeated-kv-cache-for-long-running-agents/ - Distillation without the dark – replicating black-box on-policy distillation on Baseten https://www.baseten.co/research/distillation-without-the-dark/ RESPONSIBILITIES - Define and pursue a research agenda spanning both foundational and applied work, with the applied component connected to Baseten's platform and customer needs. - Design and execute rigorous experiments, frequently at meaningful scale (multi-node, trillion parameter models). - Work with customers to translate domain-specific requirements into research problems, where relevant to your agenda. - Publish at top venues (NeurIPS, ICML, ICLR) and establish Baseten's research presence. - Collaborate with model performance and training infrastructure teams to bridge research findings and inference production systems. - Mentor junior researchers and shape the technical direction of the research organization as it grows. PREFERRED QUALIFICATIONS - Master’s or PhD research depth in machine learning, with first-author publications at top venues - Demonstrated ability to move from theory through implementation to empirical results — not exclusively theoretical or exclusively engineering work - Judgment about problem selection, the ability to distinguish research that advances a metric from research that changes how systems are built - Willingness to operate in a startup environment where the majority of research informs product decisions, with timelines measured in months rather than years - Background spanning multiple research areas (e.g., both interpretability and RL, or both systems and training methodology) - Track record of open-source contributions or community building in ML research OUR VIEW ON TALENT Many of the labs that exist today run a credentialist talent model. Concentrate the most already-legible researchers, and assume the concentration compounds. The best researchers in this field are very often not yet legible. Research engineers who have spent years inside a production stack and developed insights no PhD program teaches; PhDs working on the wrong-shaped problem at the right-shaped lab; operators who have been close to real systems long enough to see things credentialed researchers have never had to see. If you don’t have the traditional qualifications and are doing exceptional work, we’d love to chat. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: San Francisco; New York Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re looking for a customer-obsessed software engineer to come ship with us. You’ll own features like multi-node training and products like serverless reinforcement learning (RL) from conception to MVP (and from MVP to GA!). You’ll work through the stack, architecting solutions from API and UI down to our infrastructure layer. You’ll fine tune models yourself to develop an understanding of user workflows. You’ll work closely with research engineers leveraging state-of-the-art training techniques to build experiences that accelerate model development and solve for real pain points. If you’re excited to dive deep into the training, let’s talk! THE PRODUCT Take a look at what we’ve built so far: - Overview of the product so far https://www.baseten.co/blog/baseten-training-is-ga/#training-is-now-ga - Training docs overview https://docs.baseten.co/training/overview - Story of the Training product https://www.baseten.co/blog/a-q-a-from-inference-to-training-the-inside-story-of-baseten-s-newest-product/ - Research we've done https://www.baseten.co/resources/research/ EXAMPLE INITIATIVES - Checkpointing Pipeline: Our checkpointing pipeline starts with automated checkpointing, a feature that ensures that versions of models created during training are automatically backed up to the cloud. Users are able to then deploy checkpoints seamlessly into inference servers, providing point-and-click integrations into inference frameworks like vLLM and Baseten’s Inference Stack. This enables customers to quickly evaluate the performance of their checkpoints with real traffic. - Multinode training: Multinode training enables customers to easily run training jobs across multiple compute nodes, enabling users to train large models like GLM 4.7 and DeepSeek. We’ve built deeply at the Kubernetes layer to ensure that scheduling, startup, inter-node communication, and shutdown happen seamlessly under the hood and as the user expects. - Training DX: Customers come to train on Baseten because it helps them get to value fast. To do this, we ensure that the features we ship aren’t just fast, but are easy to iterate with. We enhanced Baseten’s metrics from pod-level GPU summaries to per-GPU and per-Node. We’ve built a CLI experience that caters to terminal users, and UI experiences that enable user to seamlessly manage their training jobs. RESPONSIBILITIES - Iterate like crazy - Design ergonomic APIs and abstractions to model complex resources and lifecycles - Work throughout the stack (API layer, backend and database implementation, infra layer; frontend is a plus) to implement features. - Fine-tune and deploy models to develop intuition around training workflows. - Partner closely with model developers and world-class research engineers to understand the requirements and pain points of post-training workflows. - Drive long-term improvements to improve reliability of systems and velocity of development - Fix bugs & resolve customer issues with urgency REQUIREMENTS - 5+ years experience building software applications - Deep knowledge of the web stack, databases, and distributed systems - Experience developing developer tooling or infrastructure products for external or internal users. - Good taste in product, particularly developer-oriented tools - Interest in ML/AI infrastructure and willingness to learn - Driven by high agency and ownership - Strong communication skills with the ability to bridge technical depth and business needs NICE TO HAVE - Experience launching features and products through different release cycles (MVP, Beta, GA, etc.) - Experience with model development methods and paradigms, like Supervised Fine-Tuning, Reinforcement Learning, Synthetic Data Generation, LoRA, Full Finetunes, etc. - Familiarity or experience with the open source training stack and frameworks (NCCL, PyTorch, Megatron, NemoRL, VeRL, Axolotl, HF Trainer) and distributed training techniques (FSDP, DeepSpeed). - Experience developing AI products, tooling, or agents - Frontend fluency BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: Washington, District of Columbia, United States Dexis is a dynamic professional services firm dedicated to partnering with government and community leaders both in the U.S. and internationally to achieve critical social outcomes in a rapidly changing world. At Dexis, you will experience a corporate culture of inclusiveness, respect, fairness, and trust. You will be given the means and mentorship needed to succeed, and your creativity will be rewarded. About the Position Dexis is seeking a highly experienced Strategic Consultant to support our capture and business development efforts for upcoming opportunities with the U.S. Department of State’s Bureau of Diplomatic Security (DS) – Training – Technical Security Engineering. The Advisor will play a critical role in refining our understanding of the client landscape, validating opportunity parameters, and facilitating strategic introductions to key stakeholders within the DS bureau and relevant incumbent organizations. This role is not designed to be full time and will be engaged as a 1099. Responsibilities Provide strategic insight into the organizational priorities, structure, and decision-making processes within the Bureau of Diplomatic Security. Advise Dexis leadership on client engagement strategies specific to diplomatic security and technical security engineering. Identify and facilitate introductions with relevant stakeholders throughout the capture and bid process. Validate programmatic direction, potential scope, and customer expectations for the anticipated opportunity. Participate in periodic strategy sessions and serve as a trusted advisor throughout the pre-solicitation, capture, and bid phases. Qualifications Minimum 5 years of experience working with or supporting the Department of State, with deep familiarity with the State Bureau of Diplomatic Security. Demonstrated track record of engagement with senior-level DS personnel and contract leadership. Existing relationships within the DS bureau and/or with current contract implementers in training or technical security engineering. Exceptional understanding of federal diplomatic security contracting environments. Prior experience advising capture or proposal teams targeting State Department contracts strongly preferred. Discretion, professionalism, and a strong sense of integrity in facilitating client-facing interactions. Benefits Dexis offers benefits to support employees’ health, financial security, and well-being. The benefits outlined below are for full-time, US-based positions only. These benefits include: Medical and prescription drug coverage: A choice of three UnitedHealthcare medical plans, with coverage options for employees and eligible dependents. Dental insurance: Dental coverage for employees and eligible dependents, including preventive, basic, major, and orthodontic services, subject to plan limits. Company-paid vision insurance: Vision coverage for employees and eligible dependents, with premiums paid in full by Dexis. Employer-funded health reimbursement arrangement (HRA): Employees who enroll in the Silver HRA medical plan receive an employer-funded HRA to help pay eligible in-network deductible expenses. Company-paid life and disability insurance: Basic life and accidental death and dismemberment (AD&D) insurance, plus short-term and long-term disability coverage. Optional supplemental insurance: Voluntary supplemental life and AD&D insurance options, including life insurance options for eligible dependents. Employee Assistance Program (EAP): Company-paid access to confidential counseling and legal and financial support resources for employees and their families. Health and wellness resources: Virtual care, behavioral health resources, and wellness programs available through the medical plan. Benefits assistance: Personalized support with benefit enrollment, coverage questions, claims, and finding providers through the Employee Care Center. Participation, coverage, and employee contributions are subject to applicable benefit plan terms and eligibility requirements. Dexis is on a mission to help solve today’s most pressing global political, social, and economic challenges and create a world where all people are safe and prosperous. As a Dexis employee, you will be challenged, empowered, and mentored. Our motto is “find a way or make a way” — that’s how Dexis goes “all in.” How will you? If you are passionate about this opportunity, apply now! Only those applicants who meet the above criteria will be contacted for interview. Dexis is an Equal Opportunity Employer, and does not discriminate on the basis of race, color, sex, national origin, religion, pregnancy, disability, age, genetic information, military service, veteran status, ethnicity, citizenship, sexual orientation, gender identity, marital status, childbirth and related medical conditions, including lactation, or any other protected class under applicable law.