Senior Backend Engineer, Media Intelligence at Tatari

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

23 Jan, 26

Salary

195000.0

Posted On

25 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Machine Learning, Databricks, Spark, Delta Lake, MLflow, SQL, Data Modeling, APIs, MLOps, FastAPI, Monitoring, Incident Response, Optimization, Collaboration, Feature Stores

Industry

Advertising Services

Description

Tatari is on a mission to revolutionize TV advertising. We work with some of your favorite disruptor brands—like Calm, Vuori, Rocket Money, and hundreds more—to grow their business using linear and streaming TV ads. Our platform combines sophisticated media buying with proprietary analytics to turn TV advertising into an automated, digital-like experience. Our technology and services are pushing the industry forward, enabling businesses of any size to advertise on TV. Named one of the 16 Hottest Ad Tech Companies by Business Insider and Best Places to Work by Inc. Magazine, Tatari is experiencing rapid growth. Our executive team is comprised of former founders and senior leaders at fast-rising startups like Shazam, TrueCar, AdapTV, and LiveRail and larger, more established tech companies like Amazon, Google, Meta, Microsoft, and Yahoo. We are looking for a Senior Software Engineer to join Tatari. As a Senior Engineer, you will play a leading role in the evolution and scaling of our platform. You’ll contribute to system architecture decisions, mentor junior team members, promote best practices, and ship high-quality code to production daily. At Tatari you are empowered to do your best work at a sustainable pace with a stellar group of smart, creative, and humble human beings. Come help us build a television first programmatic buying experience! Responsibilities: Architect, productionize, and own machine learning models and analytics pipelines (Databricks, Spark, Delta Lake, MLflow) with automated training, inference, and monitoring Build model observability end-to-end: inference logging, drift/data-quality monitoring, alerting, and dashboards; drive on-call readiness for ML-backed services Ship ML-powered APIs in backend services (FastAPI), ensuring low-latency, reliable online and batch serving Evolve core optimization and decisioning algorithms and their explanations to improve accuracy, stability, and user trust Partner cross-functionally (Data Science, Data Platform, Product, and external integrations) to translate research into production features with clear SLAs Mentor peers in MLOps best practices (templates, CI/CD, Databricks Connect) Qualifications: 6+ years Python; 2+ years building production ML/data systems at scale (using tools like: Spark/Databricks, Delta Lake, MLflow, Airflow) Deep SQL and data modeling; experience designing feature stores, schemas, and analytics/ML pipelines Proven experience deploying and operating ML services, including inference logging, drift detection, monitoring/alerting (Databricks, Datadog), and incident response Familiarity with applied ML for prediction, recommendation, optimization, and explainability in data-rich, real-time environments Experience working across the organization delivering on large impact initiatives Nice to have: Experience developing API frameworks (e.g. REST) Prompt engineering (prompt design, templating, RAG) and LLM evaluation frameworks Experience enhancing development processes by leveraging agentic coding tools while maintaining a high bar for quality (e.g. Cursor) Benefits: Total compensation ($170,000 - 195,000/annually) Equity compensation Health insurance coverage for you and your dependents, with minimum contribution and buy-up plans Unlimited PTO and sick days Snacks, drinks, and catered lunches at the office Team building events $1,000 annual continued education benefit $500 WFH reimbursement $150 Monthly work-related stipend FSA and commuter benefits Monthly Company Wellness Day Off Hybrid RTO of 2 days per week. THIS IS AN IN-OFFICE POSITION At Tatari, we believe in the importance of cultivating teams with diverse backgrounds and offering equal opportunities to all. We strive to create a welcoming, inclusive environment where every team member feels valued and diversity is celebrated. #LI-HYBRID

Responsibilities

Architect and productionize machine learning models and analytics pipelines while ensuring automated training and monitoring. Collaborate cross-functionally to translate research into production features and mentor peers in MLOps best practices.