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

Seattle, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

12 Jan, 26

Salary

350000.0

Posted On

14 Oct, 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, Monitoring, Alerting, Logging

Industry

Software Development

Description

ABOUT ALGOLIA Algolia is a fast growing company that helps users deliver intuitive search and discovery experiences on their websites and mobile apps. We provide APIs used by thousands of customers in more than 100 countries. Today, Algolia powers 1.5 Trillion searches a year – that’s 4 times more than Bing, Yahoo, DuckDuckGo, Baidu and Yandex combined! 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 / MLOps 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. 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. #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. While we have a global presence with physical offices in Paris, NYC, London, Sydney and Bucharest, we also offer many of our team members the option to work remotely either as fully remote or hybrid-remote employees. Please note that 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 nature of the role it may be available with either a hybrid-remote or in-office schedule. ABOUT US: Algolia prides itself on being a pioneer and market leader offering an AI Search solution that empowers 17,000+ businesses to compose customer experiences at internet scale that predict what their users want with blazing fast search and web browse experience. Algolia powers more than 30 billion search requests a week – four times more than Microsoft Bing, Yahoo, Baidu, Yandex and DuckDuckGo combined. Algolia is part of a cadre of innovative new companies that are driving the next generation of software development, creating APIs that make developers’ lives easier; solutions that are better than building from scratch and better than having to tweak monolithic SaaS solutions. In 2021, the company closed $150 million in series D funding and quadrupled its post-money valuation of $2.25 billion. Being well capitalized enables Algolia to continue to invest in its market leading platform, to better serve its thousands of customers–including Under Armor, Petsmart, Stripe, Gymshark, and Walgreens, to name just a few. WHO WE'RE LOOKING FOR: We’re looking for talented, passionate people to build the world’s best search & discovery technology. As an ownership-driven company, we seek team members who thrive within an environment based on autonomy and diversity. We're committed to building an inclusive and diverse workplace. We care about each other and the world around us, and embrace talented people regardless of their race, age, ancestry, religion, sex, gender identity, sexual orientation, marital status, color, veteran status, disability and socioeconomic background. 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 create robust, scalable AI services and own the end-to-end engineering life-cycle of machine-learning models. Responsibilities include productionizing models, deploying them on cloud platforms, and ensuring observability and reliability.