Designs, deploys, and operates production machine learning systems for identity resolution, scoring, deliverability, and personalization. Responsibilities include feature engineering, model training, real-time inference, graph database integration, monitoring, drift detection, retraining, low-latency APIs, and scalable data processing. The role also contributes to MLOps standards, GPU acceleration, and ML architecture while partnering with platform engineering.
Senior AI / Machine Learning Engineer
Location: Remote (US)
Employment Type: Full-time, W-2
Benefits: Health, vision, and dental insurance + equity options
Compensation: $135,000 USD/year
Team: Data Science & AI
Reports to: Head of Data Science & AI
Tie is building the next generation of identity resolution and marketing intelligence. Our platform connects hundreds of millions of consumers across devices, browsers, and channels—without relying on cookies—to power higher deliverability, smarter targeting, and measurable revenue lift for modern marketing teams.
At Tie, AI is not a feature—it is a core execution advantage. We operate large-scale identity graphs, real-time scoring systems, and production ML pipelines that directly impact revenue, deliverability, and customer growth.
We are looking for a Senior AI / Machine Learning Engineer to design, build, and deploy production ML systems that sit at the heart of our identity graph and scoring platform. You will work at the intersection of machine learning, graph data, and real-time systems, owning models end to end—from feature engineering and training through deployment, monitoring, and iteration.
This role is highly hands-on and impact-driven. You will help define Tie’s ML architecture, ship models that operate at sub-second latency, and partner closely with platform engineering to ensure our AI systems scale reliably.
What You’ll Do
Design and deploy production-grade ML models for identity resolution, propensity scoring, deliverability, and personalization
Build and maintain feature pipelines across batch and real-time systems (BigQuery, streaming events, graph-derived features)
Develop and optimize classification models (e.g., XGBoost, logistic regression) with strong handling of class imbalance and noisy labels
Integrate ML models directly with graph databases to support real-time inference and identity scoring Own model lifecycle concerns: evaluation, monitoring, drift detection, retraining, and performance reporting Partner with engineering to expose models via low-latency APIs and scalable services
Contribute to GPU-accelerated and large-scale data processing efforts as we push graph computation from hours to minutes
Help shape ML best practices, tooling, and standards across the team
What You’ll Bring
- 5+ years of experience building and deploying machine learning systems in production
- Strong proficiency in Python for ML, data processing, and model serving Hands-on experience with feature engineering, model training, and evaluation for real-world datasets
- Experience deploying ML models via APIs or services (e.g., FastAPI, containers, Kubernetes)
- Solid understanding of data modeling, SQL, and analytical workflows
- Experience working in a cloud environment (GCP, AWS, or equivalent)
- Experience with graph data, graph databases, or graph-based ML
- Familiarity with Neo4j, Cypher, or graph algorithms (community detection, entity resolution)
- Experience with XGBoost, tree-based models, or similar classical ML approaches
- Exposure to real-time or streaming systems (Kafka, Pub/Sub, event-driven architectures)
- Experience with MLOps tooling and practices (CI/CD for ML, monitoring, retraining pipelines)
- GPU or large-scale data processing experience (e.g., RAPIDS, CUDA, Spark, or similar)
- Domain experience in identity resolution, marketing technology, or email deliverability
- ML & Data: Python, Pandas, Scikit-learn, XGBoost
- Graphs: Neo4j (Enterprise, GDS)
- Cloud: Google Cloud Platform (BigQuery, Vertex AI, Cloud Run, Pub/Sub)
- Infrastructure: Docker, Kubernetes, GitHub Actions
- APIs: FastAPI, REST-based inference services
- Competitive compensation, including salary, equity, and performance incentives
- Opportunity to work on core AI systems that directly impact revenue and product differentiation
- High ownership and autonomy in a senior, hands-on role
- Remote-first culture with a strong engineering and data focus
- Exposure to cutting-edge problems in identity resolution, graph ML, and real-time AI systems
- Clear growth path toward Staff / Principal IC roles
At Tie, your work will not live in notebooks or experiments—it will power production systems used by real customers at scale. You will help define how AI is embedded into the company’s core platform and play a key role in making machine learning a durable competitive advantage.
Similar Jobs
Cloud • Security • Software • Cybersecurity • Automation
Drive enterprise sales growth across San Francisco, focusing on AI-native organizations and strategic accounts. Build executive relationships, develop account plans, orchestrate cross-functional sales teams, guide customers through complex DevSecOps transformations, and manage the full sales cycle from discovery through negotiation and implementation. Generate pipeline, expand existing accounts, forecast performance, conduct win/loss analysis, and position GitLab as a long-term technology partner for AI and software engineering organizations.
Top Skills:
Ai/MlDevsecopsGitlabSaaSSalesforce
HR Tech • Information Technology • Professional Services • Sales • Software
Leads integrated AMER marketing campaigns to build awareness, generate pipeline, and drive revenue for a B2B SaaS company. Responsibilities include localizing global campaigns, developing content, managing cross-functional projects, partnering with Sales and BDR teams, measuring performance, optimizing full-funnel activities, supporting customer advocacy and expansion, and providing regional market insights.
Top Skills:
AsanaB2B SaasHrisSlack
eCommerce • Real Estate • PropTech
The Senior Accountant leads day-to-day accounting operations, including general ledger, financial close, reconciliations, accounts payable, and accounts receivable. The role directly manages AP and AR teams, oversees invoicing, collections, vendor payments, and controls, and partners with the Controller on reporting and audits. It also focuses on process improvement, workflow automation, documentation, team development, and building scalable accounting operations.
Top Skills:
Accounting System IntegrationsErp/Accounting SystemsExcelWorkflow Automation Tools
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
