Spring Sale! Up to 40% off your matchmaking experience. Limited time offer.

Machine Learning Engineer

Tawkify is on a mission to redefine romantic matchmaking for the modern age. We're an established (10+ years) company generating millions in monthly revenue, and now we're poised to leverage the power of AI and LLMs to dramatically improve our service and scale.

Unlike most dating apps, Tawkify combines human connection with data-driven insights. Our team of matchmakers provides a personalized touch, but we also have a treasure trove of data – not just about people, but detailed feedback on every date, success rates, and relationship outcomes. This unique data is what will allow us to build AI solutions that were never possible before.

The Opportunity

This is a unique opportunity to be the foundational Machine Learning expert at Tawkify. You will join a collaborative team of 5 software engineers but will operate with significant autonomy, shaping the direction and execution of ML within the company. We're looking for a highly independent and proactive engineer who thrives in ambiguous environments. You will be responsible for identifying high-impact opportunities, defining the ML roadmap, establishing success metrics, and driving initiatives that leverage our unique data to create tangible business value. You won't just build models; you'll influence strategy and be instrumental in our AI-driven transformation.

What You’ll Do (Impact!)

  • Own the ML Roadmap: Define, own, and execute the Machine Learning roadmap for Tawkify, partially starting from a clean slate to build a new data strategy.
  • Influence Tech Strategy: Influence Tawkify’s technological roadmap to prioritize data collection and utilization initiatives, ensuring ML has the foundation it needs.
  • Build and Deploy Models: Design, build, evaluate, deploy, and iterate on ML models and systems using our unique datasets, focusing on practical application and business outcomes.
  • Collaborate with Engineering: Collaborate closely with the software engineering team (5 members) to integrate ML solutions seamlessly into our platform and infrastructure.
  • Partner with Product and Operations: Work directly with product and operations teams to understand user needs and matchmaker workflows, translating them into effective ML-driven features and improvements.

Example Projects You Might Tackle:

  • Enhance AI-Based Attractiveness Prediction: We present AI-generated faces to users, allowing them to rate attractiveness without revealing real user photos. We then predict attraction based on facial similarity. Improve this system to better model user preferences while preserving anonymity.
  • Redesign Profile Recommendation System: Tawkify’s recommendation engine is powered by years of profile and date feedback data. Lead major updates to this system, applying new machine learning methods to improve match quality and user experience.
  • Build a Feedback-Driven Data Flywheel: After every date, users provide structured feedback. Design a system that continuously feeds this feedback into model retraining, creating a flywheel that steadily improves matching accuracy over time.
  • Optimize Communication Strategies: Anonymity is crucial at Tawkify, and we carefully manage how we describe matches to users before their date. Analyze matchmaker communications and to help optimize the information we share, increasing user satisfaction while protecting privacy.

Why You'll Love Working Here

  • Foundational Impact: Be the key driver of Machine Learning strategy and implementation in a successful, data-rich company.
  • High Autonomy & Ownership: Define your own goals, metrics, and influence the company's direction with significant freedom and responsibility.
  • Unique Data: Work with rich, proprietary data on human interaction, matchmaking processes, and relationship outcomes – a unique dataset for ML exploration.
  • Collaborative Team: Join a supportive, talented team of software engineers in a remote-first (US-based) culture that values collaboration.
  • Modern Tech & Principles: Work within an environment guided by principles valuing simplicity, iteration speed, and leveraging modern tools (including AI coding assistants like Copilot).
  • AI-Forward: Be part of a company actively exploring and implementing AI/ML solutions across the business.

We’re Looking For

  • End-to-End Production ML Experience: You have designed, built, deployed, and iterated on machine learning systems or features in real production environments—not just prototypes or research. You can speak to specific systems you’ve owned and evolved over time.
  • Independent Project Leadership: You have taken ambiguous, high-level problems and independently turned them into deployed ML solutions. You’ve defined problem statements, created project plans, and delivered results without needing step-by-step direction. You have experience defining clear success metrics tied to business outcomes, and you know how to measure and demonstrate the value of your ML systems over time to non-technical stakeholders.
  • Hands-On Data Exploration and Experimentation: You are comfortable pulling your own data (e.g., querying a database, grabbing logs or CSVs), quickly testing ideas, and grounding your work in real data within hours—not days.
  • Strong ML Evaluation and Iteration Practices: You have set up automatic evaluation pipelines for models you deployed (e.g., offline metrics, A/B testing, model drift detection) and used those metrics to systematically improve model performance after launch. You know how to deeply analyze and prepare real-world datasets, spot quality issues, correct biases, engineer features thoughtfully.
  • Production-Grade Software Skills: You write clean, maintainable, and testable Python code. You have production experience with core ML libraries (e.g., scikit-learn, TensorFlow, PyTorch) and won’t shy away from directly contributing to application code to integrate models into the product.
  • Alignment with Tawkify’s Engineering Values: You value speed, pragmatism, simplicity, and delivering incremental value over chasing technical perfection.

Bonus Points

  • Experience with specific ML domains relevant to matchmaking (e.g., recommender systems, NLP for analyzing feedback, causal inference, learning-to-rank).
  • Experience with cloud platforms (e.g., AWS, GCP, Azure) and MLOps tools.
  • Familiarity with our existing tech stack (e.g., PostgreSQL, TypeScript) is helpful but not required.
  • Passion for building products that improve people's lives and foster human connection.

How to Apply

Please send your resume and a brief cover letter explaining why you're excited about this specific opportunity at Tawkify to careers_engineering (at) tawkify.com . Crucially, highlight examples from your past experience that demonstrate your ability to work independently, define your own roadmap, influence stakeholders, and deliver impactful ML solutions in an ambiguous environment.

Note: Check out our Engineering Principles here