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
