Senior Full Stack Engineer II

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. OVERVIEW As a Senior Machine Learning Engineer II on the Ads Response Prediction team, you will lead the design and development of core ML models that power Instacart’s ads ecosystem. This is a research-leaning role focused on theoretical problem formulation, training methodology, and model quality rather than infrastructure or full-stack engineering. You will tackle fundamental challenges in pCTR modeling such as mitigating selection bias, position bias, and optimizer’s curse in training data, improving model calibration across surfaces and domains, and advancing our multi-task learning and sequence modeling capabilities. You will also have the opportunity to shape our next-generation foundation model approach for ads ranking and contribute to cutting-edge retrieval systems like TIGER (Transformer Index for Generative Recommenders), Semantic ID and domain language models. The Ads Response Prediction team owns all systems, algorithms and ML models to ensure a relevant and engaging Ads experience to customers of all the platforms powered by Instacart. This includes search and exploration retrieval systems, sequential modeling and generative retrieval systems for next interaction recommendations, LLM integrations, relevance models, pCTR models, bidding models and incrementality models. The team optimizes for an efficient marketplace to ensure delightful customer shopping experience, desirable advertiser business outcome and Instacart Ads revenue. The team has strong ML infrastructure and MLOps support, including Delta/DBT-Spark data pipelines, Ray-based distributed training, and automated model deployment. This means you can focus your energy on advancing modeling science rather than building infrastructure. ABOUT THE JOB * Lead research and development of pCTR and conversion prediction models, with a focus on improving calibration, reducing training data biases (selection bias, position bias, optimizer’s curse), and advancing model accuracy across Instacart’s ads surfaces. * Design and implement debiasing techniques such as Mixed Negative Sampling (MNS), Inverse Propensity Weighting (IPW), counterfactual risk minimization, and calibration methods (Platt scaling, isotonic regression) to address systematic prediction biases. * Contribute to the next-generation Multi-Domain Multi-Task (MDMT) model architecture, incorporating innovations like Mixture-of-Experts (MoE), Transformer layers for sequential user behavior, and LoRA adaptors for scalable domain fine-tuning. * Drive sequence modeling initiatives including the TIGER generative retrieval system and Semantic ID representation learning, expanding their application across ads surfaces such as Product Details, Search and other placements. * Collaborate with the broader ML community in the company on the path toward Foundation Models using autoregressive user behavior prediction. * Formulate and scope ambiguous modeling problems from first principles. Translate business observations (e.g., overcalibration patterns, cold-start underperformance) into well-defined ML research directions with clear evaluation criteria. * Publish and present findings internally. Contribute to the team’s culture of technical rigor through design reviews, paper sharing, and experiment retrospectives. ABOUT YOU MINIMUM QUALIFICATIONS * PhD/Master in machine learning, statistics, computer science, information retrieval, or a closely related quantitative field. * 6+ years of combined academic and industry experience (including PhD research) applying ML to ranking, recommendation, or prediction problems at scale. * Deep understanding of CTR/conversion prediction modeling, including familiarity with architectures such as Deep & Wide, DeepFM, DCN, and multi-task learning formulations. * Strong foundation in causal inference, counterfactual reasoning, and training data bias mitigation. Ability to reason about selection bias, position bias, and propensity-based correction methods. * Proficiency in Python and deep learning frameworks (PyTorch, Tensorflow, JAX). Fluency in data manipulation tools (SQL, Spark, Pandas). * Track record of formulating ambiguous problems into well-scoped ML research directions and delivering results through rigorous experimentation. * Strong written and verbal communication skills. Ability to explain complex modeling decisions to cross-functional stakeholders including product managers and data scientists. PREFERRED QUALIFICATIONS * Experience in ads ranking or auction-based systems (pCTR, bid optimization, ROAS feedback loops, marketplace dynamics). * Hands-on experience with autoregressive sequence models for user behavior prediction, generative retrieval, or transformer-based ranking architectures. * Familiarity with learned representations such as Semantic IDs, product embeddings, or other approaches to reducing feature cardinality and cold-start challenges. * Experience with transfer learning or domain adaptation techniques (e.g., LoRA, adapter-based fine-tuning) applied to recommendation or ranking models. * Publication record in top-tier venues (KDD, WWW, RecSys, NeurIPS, ICML, SIGIR, or similar). * Experience mentoring junior engineers or shaping technical direction for a modeling team. * Familiarity with LLM-driven approaches to recommendation, including prompt-based personalization and AI-assisted model development (AutoML). #LI-Remote Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here. Offers may vary based on many factors, such as candidate experience and skills required for the role. Additionally, this role is eligible for a new hire equity grant as well as annual refresh grants. Please read more about our benefits offerings here. For US based candidates, the base pay ranges for a successful candidate are listed below. CA, NY, CT, NJ $240,000—$253,500 USD WA $230,000—$243,000 USD OR, DE, ME, MA, MD, NH, RI, VT, DC, PA, VA, CO, TX, IL, HI $221,000—$233,000 USD All other states $201,000—$212,000 USD

We're putting together a talented team to build the #1 training platform for Runners We help everyday runners become outstanding by building an incredible app providing world-class training, coaching and community for everyone, whether you're improving your 5k time or training for your first marathon. We’re growing extremely fast! In November 2023 we closed a $6.5M funding round led by JamJar with participation from Eka Ventures, Venrex and Creator Ventures. In 2024, we were selected by Apple as one of three global finalists for the iPhone app of the year, reflecting the innovation and impact of what we’ve built & in 2025 we were acquired by Strava! Our ambition is huge: to become the go-to global leading training platform for millions of runners everywhere. We’re growing with purpose and looking for people who want to build something meaningful with lasting impact. With the recent acquisition by Strava accelerating our journey, now is a really magical time to join. 🚀 THE TEAM YOU’LL JOIN We are looking for talented, creative and positive team players to join our highly-skilled cross-functional engineering team. You’ll sit in our recently formed Strength Team, where you will collaborate with our modelling engineers, as well as Team Strava, to build the next generation of strength training and redefine how athletes train. You will work closely with our CTO, and engineering leadership team to help shape the future of Runna, who will support you all along this exciting journey. We have a jam packed roadmap, with countless opportunities to champion new technologies, work on meaningful problems that impact millions of athletes, and improve existing architecture to elevate the whole of our engineering team. WHAT YOU’LL BE DOING * Architecting, building, testing and delivering new features across the full stack * Working with the Product team to identify the most suitable solution for the best customer experience * Collaborating with modelling/AI engineers to design architecture used to interface between the Runna training engine and Runna app * Always be on hand to help other team members when they need help on technical matters * Coach and support engineers in your team, providing guidance, mentorship, and code reviews without creating bottlenecks. * Help us operate more efficiently, by building and maintaining our developer tooling and CI/CD pipeline * We rotate the responsibility of releases across each team member, so you will get the opportunity to lead the process and deploy changes to production * Impacting the wider engineering team by championing new technologies and setting standards for engineering quality WHAT YOU’LL BRING TO THE TEAM: * Proficiency working with TypeScript/JavaScript * Experience with the technologies in our stack: * React Native (worked on large scale applications) * Native mobile development (Swift, Kotlin) * Cloud platforms, particularly AWS * Able to work in a highly skilled engineering team in a fast-paced, iterative environment. * 4+ years experience in your main expertise area (Frontend, Backend etc) * Comfortable picking up new things and working on technologies outside your comfort zone * Are skilled in delivering features end-to-end, from architecture design and building through to releasing, testing and supporting * Enthusiasm for our ways of working which include: * Iterative development, continuous deployment and test automation * Knowledge sharing, pair programming, collaborative design & development * Shared code ownership & cross-functional teams BONUS POINTS IF YOU HAVE: * Are experienced in deployment, releasing cycles or CI/CD * Have experience with Serverless architectures * Experience with Terraform or other IaC tooling (e.g. CDK, CloudFormation, etc.) * Have experience in open source contributions, including reporting bugs/issues in GitHub, testing new releases, or contributing to code COMPENSATION OVERVIEW & BENEFITS We’re offering a salary of £85,000 - £95,000 per year, depending on experience, plus participation in Strava's long-term incentive (stock) programs. Overview of our benefits are below: We’re also committed to continually evolving our benefits to support you as we grow. Here is a brief overview what we currently offer in the UK 🇬🇧 1. 🏢 Flexible working – we typically spend 3 days a week together in our Vauxhall office 2. 🏝️ 25 days holiday, plus bank holidays 3. 📱Free Runna & Strava subscriptions for you and 3 of your friends (get ready to be your friends fave person or save them for holiday presents!) 4. 🧘 Headspace membership 5. 💸 Money every year to spend on gear, events and the gym! 6. 🏥 Private health insurance with Bupa and workplace pension scheme 7. 💖Modern Health is a mental wellness platform and app that combines technology with professional support to improve mental well-being and reduce stress 8. 🥕Carrot fertility support - this benefits provider can provide inclusive fertility, hormonal health, and family-forming benefits to our global employee population and takes the burden off what we know can be a stressful process. Please let us know if there’s anything we can do to better accommodate you throughout the interview process - this can be from scheduling interviews around childcare commitments to accessibility requirements. We want you to show your best self in the process, so please speak to your Talent Partner!