Wissen Infotech
Website:
wissen.com
Job details:
Wissen Technology is Hiring for Senior AI/ML Engineer
About Wissen Technology:
At Wissen Technology, we deliver niche, custom-built products that solve complex business challenges across industries worldwide. Founded in 2015, our core philosophy is built around a strong product engineering mindset—ensuring every solution is architected and delivered right the first time. Today, Wissen Technology has a global footprint with 2000+ employees across offices in the US, UK, UAE, India, and Australia. Our commitment to excellence translates into delivering 2X impact compared to traditional service providers. How do we achieve this? Through a combination of deep domain knowledge, cutting-edge technology expertise, and a relentless focus on quality. We don’t just meet expectations—we exceed them by ensuring faster time-to-market, reduced rework, and greater alignment with client objectives. We have a proven track record of building mission-critical systems across industries, including financial services, healthcare, retail, manufacturing, and more. Wissen stands apart through its unique delivery models. Our outcome-based projects ensure predictable costs and timelines, while our agile pods provide clients with the flexibility to adapt to their evolving business needs. Wissen leverages its thought leadership and technology prowess to drive superior business outcomes. Our success is powered by top-tier talent. Our mission is clear: to be the partner of choice for building world-class custom products that deliver exceptional impact—the first time, every time.
Job Summary: We are seeking an experienced Senior AI/ML Engineer capable of driving complex AI/ML projects end-to-end. The ideal candidate is a hands‑on developer with strong problem‑solving skills and the ability to architect, design, and deploy scalable machine learning and generative AI solutions. This role involves working across model development, data engineering, MLOps, and AI platform design—primarily within the banking and financial services domain.
Experience: 6- 10 Years
Location: Pune
Mode of Work: Full time
Key Responsibilities:
- AI/ML Model Development
- Design, build, and optimize machine learning models for real-world use cases
- Develop models for prediction, classification, recommendation, and NLP tasks
- Build end‑to‑end ML pipelines for training, validation, and evaluation
- Generative AI & LLM Development
- Develop applications using Large Language Models (LLMs)
- Build and maintain RAG (Retrieval-Augmented Generation) pipelines
- Implement prompt engineering, embeddings, vector search, and semantic retrieval
- Fine-tune LLMs when required
- Production Deployment
- Deploy ML models into production using scalable microservices and APIs
- Build inference pipelines with high performance and low latency
- Implement monitoring, logging, and model performance optimization
- Data Engineering Collaboration
- Work with data engineering teams to build robust ML training and inference pipelines
- Ensure clean, high‑quality datasets and feature engineering workflows
- AI Platform & Architecture
- Design ML system architecture for high-volume, low-latency environments
- Integrate AI/ML solutions into enterprise-grade applications
- Research & Innovation
- Stay updated on the latest advancements in AI, ML, and Generative AI
- Evaluate and experiment with new frameworks, LLMs, and tools
Requirements:
- Strong proficiency in Python
- Hands-on experience with ML libraries/frameworks:
- TensorFlow
- PyTorch
- Scikit-learn
- Hugging Face
- Machine Learning Expertise
- Strong understanding of:
- Deep learning
- Feature engineering
- Model evaluation techniques
- Model optimization
- NLP & LLM Experience
- Working experience with transformer models and LLM APIs
- Expertise in prompt engineering, embeddings, and vector databases
- Familiarity with tools/technologies such as:
- OpenAI / Claude / Llama
- FAISS, Pinecone, Weaviate, Chroma
- MLOps & Deployment
- Experience with:
- Docker
- Kubernetes
- CI/CD for ML pipelines
- Model monitoring and versioning
- Hands-on with tools like:
- MLflow
- Kubeflow
- Airflow
- Cloud Platforms
- Hands-on experience with at least one major cloud platform:
- AWS
- Azure
- GCP
Click on Apply to know more.