Machine Learning Engineer

What You’ll Do:

· Hands-on Machine Learning Engineer who will release models in production.

· Develop classifiers, predictive models, and multi-variate optimization algorithms on large-scale datasets using advanced statistical modeling, machine learning, and data mining.

· Special focus on R&D that will be building predictive models for conversion optimization, Bidding algorithms for pacing & optimization, Reinforcement learning problems, and Forecasting.

· Collaborate with Product Management to bring AI-based Assistive experiences to life. Socialize what’s possible now or in the near future to inform the roadmap.

· Responsible for driving all aspects of ML product development: ML modeling, data/ML pipelines, quality evaluations, productization, and ML Ops.

· Create and instill a team culture that focuses on sound scientific processes and encourages deep engagement with our customers.

· Handle project scope and risks with data, analytics, and creative problem-solving.

What you require:

· Solid foundation in machine learning, classifiers, statistical modeling and multivariate optimization techniques

· Experience with control systems, reinforcement learning problems, and contextual bandit algos.

· Experience with DNN frameworks like TensorFlow or PyTorch on large-scale data sets.

· TensorFlow, R, scikit, pandas

· Proficient in one or more: Python, Java/Scala, SQL, Hive, Spark

· Good to have - Git, Docker, Kubernetes

. GenAI, RAG pipelines a must have technology

. Cloud based solutions is good to have

· General understanding of data structures, algorithms, multi-threaded programming, and distributed computing concepts

· Ability to be a self-starter and work closely with other data scientists and software engineers to design, test, and build production-ready ML and optimization models and distributed algorithms running on large-scale data sets.

Ideal Candidate Profile:

· A total of 10+ years of experience, including at least 5 years in technical roles involving Data Science, Machine Learning, or Statistics.

· Masters or B.Tech in Computer Science/ Statistics

· Comfort with ambiguity, adaptability to evolving priorities, and the ability to lead a team while working autonomously.

· Proven management experience with highly diverse and global teams.

· Demonstrated ability to influence technical and non-technical stakeholders.

· Proven ability to effectively manage in a high-growth, matrixed organization.

· Track record of delivering cloud-scale, data-driven products, and services that are widely adopted with large customer bases.

· An ability to think strategically, look around corners, and create a vision for the current quarter, the year, and five years down the road.

· A relentless pursuit of great customer experiences and continuous improvements to the product. ​