Software Engineer I - AI and ML

Zinnia - Employee Referral; Dadri; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

Zinnia is seeking a passionate Python and AI/ML Engineer in Dadri, India. The ideal candidate will have at least 4 years of hands-on experience building intelligent systems, focusing on Generative AI and machine learning pipelines.

Your role will involve designing, developing, and deploying AI models and APIs, optimizing data interactions, and staying updated with AI advancements. Join us to create impactful AI solutions that enhance our offerings.

Qualifications

• Minimum 4 years of hands-on experience building intelligent systems.
• Experience with Generative AI, scalable ML pipelines, and production-grade systems.
• Strong background in design, development, and deployment of machine learning models.

Responsibilities

• Design, develop, and deploy machine learning models and Generative AI solutions.
• Own end-to-end ML pipelines and collaborate with teams to translate business requirements.
• Build robust RESTful APIs to expose ML models and AI services.

Skills

Python

Generative AI

NLP & Search / Ranking

API Development

Databases

Tools

NumPy

Pandas

FastAPI

Scikit-learn

PyTorch

TensorFlow

XGBoost

DBSCAN

spaCy

BERT

FAISS

Elasticsearch

PostgreSQL

MongoDB

Job description

Zinnia is the leading technology platform for accelerating life and annuities growth. With innovative enterprise solutions and data insights, Zinnia simplifies the experience of buying, selling, and administering insurance products. All of which enables more people to protect their financial futures. Our success is driven by a commitment to three core values: be bold, team up, deliver value – and that we do. Zinnia has over $180 billion in assets under administration, serves 100+ carrier clients, 2500 distributors and partners, and over 2 million policyholders.

WHO YOU ARE

You are a passionate Python and AI/ML Engineer with minimum 4 years of hands‑on experience building intelligent systems. You thrive in fast‑paced environments, love solving complex problems with data and algorithms, and take pride in delivering AI solutions that create real business impact. You have experience with cutting‑edge Generative AI, scalable ML pipelines, and production‑grade systems and you’re energized by working at the frontier of what AI can do.

WHAT YOU'LL DO

• Design, develop, and deploy machine learning models and Generative AI solutions — including classification, clustering, summarization, search & ranking, and information extraction.
• Own end‑to‑end ML pipelines — from data ingestion and preprocessing through model training, deployment, and production monitoring.
• Collaborate with cross‑functional teams to translate business requirements into AI‑driven features — applying NLP, outlier detection, and deep learning techniques where applicable.
• Build robust, scalable, and well‑documented Python‑based RESTful APIs to expose ML models and AI services in production environments.
• Optimize database interactions and ensure efficient data storage and retrieval for AI applications across SQL and NoSQL systems.
• Stay current with the latest advances in AI/ML — integrating emerging approaches such as RAG pipelines, LLM fine‑tuning, and vector search into live products.

WHAT YOU'LL NEED

Python — Strong hands‑on proficiency for building, scripting, and deploying AI/ML systems. Proficiency with NumPy, Pandas, FastAPI, Scikit‑learn, PyTorch, TensorFlow, XGBoost, DBSCAN.

Generative AI (2+ yrs) — Hands‑on experience building with LLMs, prompt engineering, RAG pipelines, summarization, and AI‑powered features.

NLP & Search / Ranking — Processes language and builds relevance engines — NER, embeddings, semantic search, and ranking models using spaCy, BERT, FAISS, Elasticsearch.

API Development — Designs and ships secure, well‑documented RESTful APIs exposing ML models as production‑ready services. Familiarity with REST, FastAPI, OAuth2, Swagger.

Databases — Proficient in SQL and NoSQL stores for structured and unstructured data pipelines supporting AI workloads. Experience with PostgreSQL, MongoDB, vector databases.

GOOD TO HAVE

Cloud Platforms — Deploys and scales AI workloads on AWS, Azure, or GCP.

MLOps — Manages the ML lifecycle — tracking, versioning, and pipeline automation using MLflow, Kubeflow, CI/CD.

Containerization & Orchestration — Packages and scales AI services using containers and cluster management with Docker, Kubernetes.

At Zinnia, we are committed to fostering an inclusive and diverse workplace. This statement is asked solely for reporting purposes and will not influence the evaluation of your application or hiring decision.