Senior AI / MLOps Engineer – e-Commerce Search & Information Retrieval at ALGOLIA INC

Seattle, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

23 Feb, 26

Salary

350000.0

Posted On

25 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Go, Docker, Kubernetes, AWS, GCP, CI/CD, REST, gRPC, Kafka, Spark, MLflow, Feature Store, Model Evaluation, A/B Testing, Drift Detection

Industry

Software Development

Description

At Algolia, we’re proud to be a pioneer and market leader in AI Search, empowering 17,000+ businesses to deliver blazing-fast, predictive search and browse experiences at internet scale. Every week, we power over 30 billion search requests — four times more than Microsoft Bing, Yahoo, Baidu, Yandex, and DuckDuckGo combined. In 2021, we raised $150 million in Series D funding, quadrupling our valuation to $2.25 billion. This strong foundation enables us to keep investing in our market-leading platform and serving incredible customers like Under Armour, PetSmart, Stripe, Gymshark, and Walgreens. THE MISSION We are building the next generation of AI powered search products. We make AI explainable and we help customers make data driven decisions through. Work with the product function to guide product development through use of analytics and experimentation. You will be an integral part of building the future of AI search. If you’re passionate about turning product data into actionable insights and driving product success, we’d love to hear from you. THE OPPORTUNITY We are seeking a skilled Senior AI / ML Ops Engineer to enable our Data Scientists to move faster and our customers to receive smarter search & discovery experiences by turning prototypes into robust, scalable, and observable AI services. You will own the end-to-end engineering life-cycle—packaging, deploying, operating, and continuously improving machine-learning models that power search ranking, recommendations, and related information-retrieval features on our e-commerce platform. What you'll be doing: Productionization & Packaging: Convert notebooks and research codebase into production-ready Python and Go micro-services, libraries, or kubeflow pipelines, and design reproducible build pipelines (Docker, Conda, Poetry) and manage artefacts in centralized registries. Scalable Deployment: Orchestrate real-time and batch inference workloads on Kubernetes, AWS/GCP managed services, or similar platforms, ensuring low latency and high throughput, and Implement blue-green / canary rollouts, automatic rollback, and model versioning strategies (SageMaker, Vertex AI, KServe, MLflow, BentoML, etc.). MLOps & CI/CD: Build and maintain CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, Argo) covering unit, integration, data-quality, and performance tests, and Automate feature store updates, model retraining triggers, and scheduled batch jobs using Airflow, Dagster, or similar orchestration tools. Observability & Reliability: Define and monitor SLIs/SLOs for model latency, throughput, accuracy, drift, and cost, and Integrate logging, tracing, and metrics (Datadog etc.) and establish alerting & on-call practices. Data & Feature Engineering: Collaborate with data engineers to create scalable pipelines that ingest clickstream logs, catalog metadata, images, and user signals, and Implement real-time and offline feature extraction, validation, and lineage tracking. Performance & Cost Optimization: Profile models and services; leverage hardware acceleration (GPU, TPU), libraries (ONNX, OpenVINO), and caching strategies (Redis, Faiss) to meet aggressive latency targets, and Right-size clusters and workloads to balance performance with cloud spend. Governance & Compliance: Embed security, privacy, and responsible-AI checks in pipelines; manage secrets, IAM roles, and data-access controls via Terraform or CloudFormation, and Ensure auditability and reproducibility through comprehensive documentation and artifact tracking. Collaboration & Mentorship: Partner closely with Data Scientists, Product Owners, and Site Reliability Engineers to align technical solutions with business goals, and Coach junior engineers on MLOps best practices and contribute to internal knowledge-sharing sessions. Role Requirements: Spend 1-2 days per week in a local coworking space to collaborate with your teammates in person. 5+ years of experience in software engineering with 2+ years focused on deploying ML/AI systems at scale. Strong coding skills in Python (preferred) and at least one statically typed language (Go preferred). Hands-on expertise with containerization (Docker), orchestration (Kubernetes/EKS/GKE/AKS), and cloud platforms (AWS, GCP, or Azure). Proven record of building CI/CD pipelines and automated testing frameworks for data or ML workloads. Deep understanding of REST/gRPC APIs, message queues (Kafka, Kinesis, Pub/Sub), and stream/batch data processing frameworks (Spark, Flink, Beam). Experience implementing monitoring, alerting, and logging for mission-critical services. Familiarity with common ML lifecycle tools (MLflow, Kubeflow, SageMaker, Vertex AI, Feature Store, etc.). Working knowledge of ML concepts such as feature engineering, model evaluation, A/B testing, and drift detection. #LI-Hybrid Algolia is an Equal Opportunity Employer and does not discriminate on the basis of race, color, religion, sex, age, national origin, military status, veteran status, disability status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. The annual base salary compensation range for this role reflects US market pay data within this location. The exact compensation offered for this role may vary depending on specific location and job-related knowledge, technical skills, and experience; and is only one part of our Total Rewards philosophy to compensate and recognize employees for their work. Remote US: Base Salary Pay Range $200,000—$350,000 USD FLEXIBLE WORKPLACE STRATEGY: Algolia’s flexible workplace model is designed to empower all Algolians to fulfill our mission to power search and discovery with ease. We place an emphasis on an individual’s impact, contribution, and output, over their physical location. Algolia is a high-trust environment and many of our team members have the autonomy to choose where they want to work and when. We have a global presence with offices in Paris, NYC, London, Sydney and Bucharest, however we also offer many of our team members the option to work remotely either as fully remote or hybrid-remote employees. Positions listed as "Remote" are only available for remote work within the specified country. Positions listed within a specific city are only available in that location - depending on the role it may be available with either a hybrid-remote or in-office schedule. WE’RE LOOKING FOR SOMEONE WHO CAN LIVE OUR VALUES: GRIT - Problem-solving and perseverance capability in an ever-changing and growing environment. TRUST - Willingness to trust our co-workers and to take ownership. CANDOR - Ability to receive and give constructive feedback. CARE - Genuine care about other team members, our clients and the decisions we make in the company. HUMILITY - Aptitude for learning from others, putting ego aside. We’re looking for talented, passionate people to help build the world’s best search and discovery technology. We value autonomy, diversity, and collaboration. We’re committed to creating an inclusive workplace where everyone is respected and supported—regardless of race, age, ancestry, religion, sex, gender identity, sexual orientation, marital status, color, veteran status, disability, or socioeconomic background. PLEASE REVIEW OUR POLICY FOR AI USE IN INTERVIEWS - https://www.algolia.com/blog/algolia/algolia-ai-guidelines-for-candidates IMPORTANT NOTICE FOR CANDIDATES - Recruitment Fraud Notice We’ve recently seen an increase in recruitment scams targeting job seekers. To help protect yourself, please keep the following in mind: Our open positions may appear on third-party job boards, but the best way to apply safely is directly through our careers page. All genuine communication from Algolia will come from an @algolia.com email address. If you receive an email from someone claiming to work at Algolia who does not have an @algolia.com email address, please do not respond or share any personal information. We’ll never ask for payments, purchases, or financial details during the hiring process. READY TO APPLY? If you share our values and our enthusiasm for building the world’s best search & discovery technology, we’d love to review your application!

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Responsibilities

The Senior AI / MLOps Engineer will enable Data Scientists to accelerate their work and enhance customer search experiences by transforming prototypes into scalable AI services. This role involves managing the entire engineering lifecycle, including packaging, deploying, and improving machine-learning models for search ranking and recommendations.