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