Senior Machine Learning Engineer

We are looking for a Senior Machine Learning Engineer to design, own, and scale predictive systems that power VIS.X - programmatic advertising platform.
You will take end-to-end responsibility for high-impact ML initiatives (e.g., pricing optimization, bid prediction, performance forecasting, delivery optimization) and translate complex business problems into robust, production-grade machine learning systems.
This is a senior individual contributor role with leadership potential. You will help shape our ML architecture, standards, and long-term AI strategy, with the opportunity to grow into a team lead role as we expand our data science capabilities.
Requirements:

5+ years of experience in machine learning / applied ML roles with production ownership

Proven track record of deploying and maintaining ML systems in real-world environments

Strong Python skills (e.g., pandas, scikit-learn, PyTorch/TensorFlow)

Solid knowledge of statistics, experimentation design, and model evaluation

Experience working with large-scale datasets and performance-critical systems

Understanding of MLOps principles (model lifecycle, monitoring, CI/CD integration, retraining pipelines)

Strong problem ownership mindset - ability to independently structure ambiguous challenges

Ability to translate business trade-offs into modeling decisions

Experience in AdTech, marketplaces, or auction-based systems is a plus

Experience working in high-scale, real-time systems is a plus

Responsibilities:

Take ownership of machine learning problems from concept to production

Design, build, and deploy predictive models (e.g. pricing, bidding, optimization, forecasting)

Develop scalable feature engineering and data pipelines for large-scale datasets

Define experimentation frameworks (A/B testing, offline validation, model comparison)

Ensure production-grade MLOps: monitoring, retraining, drift detection, reliability

Collaborate closely with DevOps, Product, Engineering teams to align ML with business impact

Quantify model impact on revenue, margin, and performance KPIs

Contribute to building our long-term ML architecture and best practices

What we offer:

Comfortable environment, challenging tasks and a long-term interesting project;

Covered 20 days of vacation;

Working with top notch equipment;

Bookkeeping by a professional accountant;

Help and support from our caring HR-team;

Originally posted on Himalayas