Senior Machine Learning Engineer, Search & Recommendations

Senior Machine Learning Engineer II, Search & Recommendations Ranking

Instacart

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 The Search & Personalization ML team is Instacart’s engine for state-of-the-art multi-task, multi-objective ranking—unifying search, discovery, recommendation, ads, and merchandising into a single value-aware platform. Partnering with world-class engineers, scientists, and PMs, we build the ranking backbone that powers every pixel of the shopping journey, optimizing not just for clicks, but for incremental GTV, basket lift, and retention over the long run. What We’re Building * Foundational Ranking Backbone Models: Multi-task/multi-objective models (shared encoders + task heads) that jointly learn relevance, conversion, margin contribution, churn risk, and ad quality, enabling consistent decisions across search and recommendations. * Value-Aware Optimization: Uplift and long-horizon value models that steer decisions toward incrementality and LTV, with calibrated constraints on quality, diversity, fairness, and spend pacing—plus guardrails for safe exploration. * LLM-Enhanced Retrieval & Features: Using LLMs to enrich query and item semantics for long-tail recall, generate features for cold-starts, and feed the ranker with reasoning-rich context, while remaining the source of truth for final ordering. Our commitment to AI innovation is reflected in our recent publications and research contributions to the field.   About the Job * Architect the ranking backbone that unifies query understanding, personalization, multi-objective ranking, ads, and merchandising into a single adaptive platform. * Design and build a search autosuggest system optimized for personalization and value-based relevance. * Design long-horizon objective functions (e.g., incrementality, LTV, habit formation) and build uplift/causal value models that move beyond short-term engagement. * Develop production-grade Multi-Task Learning (e.g., shared encoders, MMOE/PLE task heads) to jointly learn relevance, propensity, margin, and churn risk—ensuring calibration, constraints, and explainability. * Own the inference layer: goal-aware re-rankers, diversity and quality constraints, safe exploration, and millisecond-class latency optimization. * Advance evaluation practices: online experiments, long-horizon cohort metrics, counterfactual evaluations, and attribution pipelines for tracking incremental GTV and retention. * Partner across ads, infrastructure, product, and design teams to translate business goals into ranking policies and measurable ROI. * Mentor ML engineers to build expertise in ranking, causal inference, and scalable serving systems.   About You Minimum Qualifications * 5+ years applying ML at scale (3+ years in technical leadership), with a proven track record improving ranking or recommendation systems in production. * Demonstrated success in applying multi-objective or constrained optimization to balance relevance, revenue, margin, and user experience; experience with online testing and attribution beyond CTR. * Strong coding (Python) and data fluency (SQL/Pandas), with expertise in classic ML techniques (e.g., XGBoost) and deep learning frameworks (TensorFlow/PyTorch). * Excellent analytical skills and strong cross-functional communication abilities. Preferred Qualifications * Expertise in multi-task learning architectures (e.g., MMOE/PLE, shared encoders), calibration, counterfactual evaluation, uplift/causal modeling, and/or contextual bandits for exploration. * Experience building low-latency ranking services, including feature stores, caching, vector + lexical retrieval, re-ranking, and A/B testing infrastructure, with expertise in constraint-aware inference. * Hands-on experience with LLMs as feature/recall enhancers (e.g., embeddings, adapter tuning) while maintaining clarity on when the ranker should arbitrate. 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 $207,000—$253,500 USD WA $198,000—$243,000 USD OR, DE, ME, MA, MD, NH, RI, VT, DC, PA, VA, CO, TX, IL, HI $190,000—$233,000 USD All other states $173,000—$212,000 USD

Senior Machine Learning Engineer - Personalisation

Deliveroo

SENIOR MACHINE LEARNING ENGINEER Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Global engineering teams tackle complex technical challenges across a global, three-sided marketplace, building and scaling systems that serve millions of customers, riders and partners every day. We’re looking for a Senior Machine Learning Engineer to join our London office as part of a Global DoorDash engineering team (working hybrid, 3 days in the office). You’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the search and personalization experiences at the heart of our fast-growing New Verticals business, encompassing grocery, convenience, and retail delivery. WHAT YOU’LL DO You’ll be joining the New Verticals Personalisation team (Search & Recommendations). This team sits at the heart of how customers discover and shop across grocery, convenience, and retail categories, and is a key driver of the growth of Deliveroo's expanding New Verticals business. Working across the wider DoorDash engineering team, you’ll help shape intelligent, consumer-facing experiences that solve real customer problems at scale. This role spans a broad range of cutting-edge machine learning challenges, including modern recommendation and ranking systems, real-time decisioning as well as GenAI-powered experiences. Here’s what your day-to-day might look like: * Design and build production-grade machine learning and optimisation systems that power Deliveroo's New Verticals search and recommendations at scale. * Partner with engineering and product leaders to help shape the product roadmap leveraging ML. * Provide technical leadership across multiple product areas, identifying and prioritising opportunities for high-impact algorithmic improvements. * Mentor junior team members, and lead cross functional pods to generate collective impact across the business. WHAT YOU’LL NEED TO THRIVE Our ideal candidate will bring strong expertise in some of these areas and curiosity to grow in others: * Proven track record of designing and shipping impactful algorithms that deliver measurable business outcomes in a production environment. * Deep expertise in applied ML for Search/NLP/IR/RecSys - both classical and deep learning based. Additional familiarity with explore/exploit/MAB algorithms, LLMs, and causal inference techniques are a plus. * Machine learning background in Python; experience with PyTorch or TensorFlow preferred. * Ability to think holistically about business problems, moving beyond technical implementation to influence long-term strategy and roadmap. * Excellent communication and stakeholder management skills, with the ability to influence both technical and non-technical leaders across the global organisation. WHY JOIN US? At Deliveroo, you'll do work that matters—solving real-world problems in a three-sided marketplace that’s constantly evolving. We’re food lovers, problem solvers, community builders and more, brought together by a shared drive to make things better. Working here you can expect to: 🔧 Solve meaningful problems at real scale Work on a complex, always-on marketplace that impacts millions every day. 🌱 See your impact, fast Ship, test and improve ideas quickly in a low-hierarchy, high-ownership environment. 🧠 Grow through challenge and ownership Take on big, ambiguous problems and accelerate your career with strong support. 🌎 A culture built for builders High standards, collaboration, flexible working and continuous learning. 💰 Share in the success you help create Competitive salary and equity options, so you’re rewarded for the impact you make. ➡️ Want a deeper look at how we build? Check out our Tech Blog. OUR GLOBAL STRUCTURE Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. DIVERSITY, EQUITY AND INCLUSION At Deliveroo, we know that a great workplace reflects the world around us and that true diversity and inclusion make us stronger, more creative, and better at what we do. We’re committed to fostering an environment where everyone can do their best work and feel they belong. We believe in equality of opportunity and welcome candidates from all backgrounds regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion, or belief. If you have a disability or long-term health condition and need support to apply for one of our roles, or require any reasonable adjustments during the recruitment process, you’ll have the opportunity to let us know once you’ve submitted your application. We’ll share details on how to request support so we can ensure you have a fair and equitable experience. If you’re excited about making a real impact in a fast-moving marketplace and growing your career alongside ambitious, supportive teams, we’d love to hear from you!

Senior Machine Learning Engineer

Reddit

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com. At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including: * Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities * Intelligent advertising systems including ranking, bidding, measurement, and optimization * Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals * Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems * Applied AI and LLM-driven experiences that improve relevance, discovery, and user engagement You’ll work on high-impact systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes. What You’ll Do * Design, build, and deploy production-grade machine learning models and systems at scale * Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring * Build scalable data and model pipelines with strong reliability, observability, and automated retraining * Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems.  * Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions * Improve system performance across latency, throughput, and model quality metrics * Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph & transformers based, and LLM evaluation/alignment  * Contribute to technical strategy, architecture, and long-term ML roadmap Basic Qualifications * 3-5+ years of experience building, deploying, and operating machine learning systems in production * Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals * ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs) * Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow) * Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure * Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions * Experience improving measurable metrics through applied machine learning Preferred Qualifications * Experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems * Familiarity with distributed systems and large-scale data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.) * Experience working with real-time systems and low-latency production environments * Background in feature engineering, model optimization, and production monitoring * Experience with LLM/Gen AI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale * Advanced degree in Computer Science, Machine Learning, or related quantitative field Potential Teams * Ads Measurement Modeling  * Ads Targeting and Retrieval * Advertiser Optimization * Ads Marketplace Quality * Ads Creative Effectiveness * Ads Foundational Representations * Ads Content Understanding * Ads Ranking * Feed Relevance * Search and Answers Relevance * ML Understanding * Notifications Relevance Benefits * Comprehensive Healthcare Benefits and Income Replacement Programs * 401k with Employer Match * Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support * Family Planning Support * Gender-Affirming Care * Mental Health & Coaching Benefits * Flexible Vacation & Paid Volunteer Time Off * Generous Paid Parental Leave  Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/. To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $216,700—$303,400 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors. Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.