Lead Machine Learning Engineer

ZS is a place where passion changes lives. As a management consulting and technology firm focused on improving life and how we live it, our most valuable asset is our people. Here you’ll work side‑by‑side with a powerful collective of thinkers and experts shaping life‑changing solutions for patients, caregivers and consumers worldwide. ZSers drive impact by bringing a client first mentality to each and every engagement. We partner collaboratively with our clients to develop custom solutions and technology products that create value and deliver company results across critical areas of their business. Bring your curiosity for learning; bold ideas; courage and passion to drive life‑changing impact to ZS. Our most valuable asset is our people . At ZS we honor the visible and invisible elements of our identities, personal experiences and belief systems—the ones that comprise us as individuals, shape who we are and make us unique. We believe your personal interests, identities, and desire to learn are part of your success here. Learn more about our diversity, equity, and inclusion efforts and the networks ZS supports to assist our ZSers in cultivating community spaces, obtaining the resources they need to thrive, and sharing the messages they are passionate about. What You’ll Do Model Development & Optimization – Design, train, and fine‑tune state‑of‑the‑art NLP models, including large language models (LLMs), to address use cases such as text classification, information extraction, summarization, sentiment analysis, and question answering. Model Validation & Quality Assurance – Conduct rigorous testing and validation of NLP models, ensuring robust performance under diverse scenarios and datasets. Develop automated evaluation pipelines using comprehensive metrics and real‑world test cases. Scalable Deployment – Collaborate with backend engineers to integrate NLP models into production through RESTful APIs and microservices. Architect scalable, efficient solutions that deliver reliable performance in high‑traffic production environments. Data Pipelines & Workflow Automation – Build and maintain efficient, event‑driven data pipelines using tools such as Kafka, Spark, or similar technologies. Ensure seamless data ingestion, processing, and integration to enable real‑time or batch‑driven NLP workflows. Thought Leadership & Innovation – Stay at the forefront of NLP advancements, including emerging trends in LLMs, fine‑tuning strategies, and transformer‑based architectures. Propose and implement innovative approaches to solve complex language processing challenges. Technical Mentorship & Team Collaboration – Lead by example through high‑quality code contributions and participation in peer code reviews. Contribute to the development of engineering best practices, fostering a culture of technical excellence and continuous learning within the team. What You’ll Bring 5+ years of experience in API development, including the design and integration of scalable and efficient APIs in production environments. Proven experience working with diverse database technologies, including SQL, NoSQL, and vector databases. Experience with graph databases is a strong advantage. NLP Expertise – Proficiency in leading NLP libraries such as spaCy, NLTK, Hugging Face Transformers, and SentenceTransformers. Programming: Advanced skills in Python (required), with experience using backend frameworks such as Flask, FastAPI, or Django. Classical NLP: Solid understanding of classical NLP techniques such as TF‑IDF, word embeddings, and topic modeling. Data Engineering: Hands‑on experience with data engineering concepts and tools, particularly event streaming platforms like Kafka, to build efficient pipelines and support real‑time model updates. Cloud and DevOps: Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and containerization/orchestration tools like Docker and Kubernetes is a strong plus. Additional Skills Product‑centric mindset: Experience contributing to product development processes, including participating in daily standups, collaborating on user stories, and creating solutions that prioritize end‑user experience and elegance. Problem‑solving: Strong analytical skills to address complex challenges and deliver scalable, impactful solutions. Collaboration: Exceptional interpersonal and communication skills, with the ability to translate technical concepts for technical and non‑technical audiences. 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