Machine Learning Engineer II

Role Overview

• Utilize AI techniques, including machine learning, deep learning, generative AI, and statistical modeling, to develop and implement solutions for tackling real-world problems such as ranking, chatbot, intent recognition, agentic AI systems, recommender systems, computer vision, NLQ etc.
• Apply strong coding skills, analytical abilities, and innovative thinking to quickly understand new domains and transform creative ideas into functional solutions.
• Employ statistical and data science methods to make data-driven decisions.
• Manipulate large data sets for business insights and drive actionable solutions.
• Utilize appropriate methods and approaches to develop practical solutions for the business.
• Structure work, frame issues, and produce analyses/ML models/Compound AI systems that answer complex business questions in a pragmatic approach.
• Communicate complex data science topics in a clean & simple way to multiple partners and senior leadership.
• Collaborate with a global team across different continents to achieve project goals.

Requirements

• 6+ years of experience with a bachelor’s degree or equivalent, or 3+ years with a master’s degree or equivalent.
• Proven ability to conceptualize business problems and solve them through data science solutions.
• Proven knowledge of AI techniques such as Bayesian methods, Clustering, Ensemble tree models, NLP, etc., with an excellent grasp of statistical concepts and methods.
• Good understanding of LLMs, guardrails, RAG, agentic AI.
• Strong passion for solving problems and finding patterns and insights within structured and unstructured data.
• Industry experience in leveraging AI techniques on real-world large data sets.
• Understanding of the concepts and steps involved in working with real-world large data sets: from domain-specific problem understanding, data preparation, travel-related data processing, feature engineering, data structures for ML, data pipelining, modeling, offline evaluation, online evaluation, and monitoring.
• Strong knowledge of hands-on practice in Python.
• Familiarity with popular machine learning libraries and frameworks such as scikit-learn, Hugging Face, PyTorch and TensorFlow.
• Experience with MLFlow, AWS SageMaker and Bedrock is preferred.
• Familiar with MLOps concept.
• Comfortable with data cleansing using SQL and PySpark.
• Good written and oral communication skills, including the ability to communicate across business areas and increase overall knowledge across the organization.
• Experience with feature stores, machine learning models as service, and monitoring dashboards is a plus.
• Some infrastructure knowledge (AWS, Kubernetes) and cost-awareness are a plus.

Tech Stack

• AWS
• Kubernetes
• PySpark
• Python
• PyTorch
• Scikit-Learn
• SQL
• Tensorflow

Benefits

• health and welfare insurance plans
• retirement programs
• parental leave
• adoption assistance
• wellbeing resources to support you and your immediate family
• travel perks: get a choice of deals each week from major travel providers on everything from flights to hotels to cruises and car rentals
• access to over 20,000 courses on our learning platform
• leadership courses
• new job openings available to internal candidates first.
• champion Inclusion in every aspect of our business