Engineering Manager, AI Solutions

Job Description

As the Engineering manager, you will be managing the roadmap priorities for AI/MLSolution andwill bepoint of contactfor all technical issues and decisions, while managing stakeholders and partners across the organization. Provide technical leadership manage a high-performing engineering team to build and scale our next generationAI Solutions. Hire and directly lead a diverse team of top-tier ML and software engineers, taking charge of allfacetsof AI Products Design, Build,optimize, fine-tune Generative AI/LLM models/AI Solutions that can be integrated withnumerousapplications, support thousands of tenants, andoperateat scale in production to support variousPaypalAI Personalization initiatives Ensure high code quality, performance, and reliability through rigorous testing, code reviews, and adherence to software development best practices. Drive innovation by researching and incorporatingstate-of-the-artmachine learning techniques, tools, and frameworks into the platform. Effective communication, listening, interpersonal, influencing, and alignment driving skills; able to convey important messages in a clear and compelling manner Collaborate with cross-functional teams including product managers, data scientists, and software engineers and stakeholders to define platform requirements and priorities. Develop and evolve engineering processes and collaboration models tooptimizeteam efficiency and collaboration Mentor team members,providetechnical guidance, and foster a culture of collaboration, innovation, and continuous learning. Stay up to date with the latest advancements in AI/ML technology and industry trends andleveragethis knowledge to enhance the platforms capabilities What Do You NeedtoBring Qualifications Proven experience in leading or managing machine learning/AI teams, witha track recordof building successful AI solutions and productizing ML Models, Features Stores Solidtrack recordof over-achieving engineering and platform delivery and scaling targets in high volume, innovative and fast-paced high-pressure environment; proven results in delivery on platform products. Masters / bachelor s in computer science, Computer engineering, Machine Learning, Data Mining, Information Systems, or related disciplines, with technicalexpertisein one or more of the above-mentioned areas or equivalent practical experience. Experience developing Gen AI applications/services usingPrompt Engineering, LLMs, and fine-tuning methodsfor sophisticated business use caseswithlarge amountsof unstructured data. Strong background in deep learning techniques, particularly in NLP and Vision Proficiencyin multiple Programming/scripting languages,i.e.Python, Java, Scala,SQL, NoSQL (like HBase, Redis, Aerospike) Strongproficiencyin machine learning concepts, algorithms, and techniques, with hands-on experience in developing and deploying machine learning models. Expertisein buildingMLpipelines with Big Data technologies such as Hadoop, Spark, HBase, Kafka. Good understanding of distributed systems, data streaming, complex event Processing, NoSQL solutions for creating and managing data integration pipelines for batch and Real Time data needs. Experience with machine learning libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, etc. Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes). Experience in Azure is a plus Strong communication, listening, interpersonal, influencing, and alignment driving skills; able to convey important messages in a clear and compelling manner Demonstrated leadership abilities, including the ability to inspire, mentor, and empower team members to achieve their full potential. Preferred Prior experience in Content Understanding, enrichment, entity resolution or knowledge graph Strong background in MLOps and experimentation frameworks Extensive experience with concurrent, parallel, and distributed computing, including performance tuning and optimization for large-scale applications