Machine Learning Engineer

About Company :

Naveera is a trusted global engineering partner delivering Data Engineering, Generative AI, Application Development and IT Infrastructure solutions. With over 15 years of experience in IT services and consulting. we help organizations transform raw data into deployable business value.

Our approach emphasises Production over Pilots we dont stop at proof-of-concepts; we engineer systems that go live, scale reliably, and deliver measurable outcomes. With our CoE-driven delivery model, product engineering DNA, and a scalable talent acquisition engine, we align deeply with enterprise demands for performance, compliance, continuity and innovation.

From Digital Health to Financial Services, and E-Commerce to Technology, we serve a diverse industry base and back every engagement with proven frameworks, low-attrition teams and agile global delivery. At Naveera, we empower clients to turn challenge into growth, data into insight and concepts into platforms.

Specialties :

Role Overview :

We are looking for a highly skilled Machine Learning Engineer with strong expertise in both traditional machine learning and modern Generative AI (LLMs) to design, build, and deploy scalable AI solutions. The ideal candidate will work on large-scale structured and unstructured data, enabling intelligent automation and insights, particularly in domains such as insurance (claims, underwriting, fraud detection).

Key Responsibilities :

- Design, develop, and deploy end-to-end machine learning and deep learning models for real-world business problems

- Build scalable solutions for large-volume data processing (structured & unstructured)

- Develop and optimize Generative AI applications using LLMs (e.g., RAG pipelines, copilots, summarization, Q&A systems)

- Implement predictive analytics models such as classification, regression, clustering, and anomaly detection

- Work on insurance-focused use cases, including :

1. Claims anomaly/fraud detection

2. Risk scoring and underwriting support

3. Document processing (OCR + NLP pipelines)

- Build and maintain data pipelines and feature engineering workflows

- Fine-tune and evaluate LLMs and embedding models for domain-specific use cases

- Ensure model performance, scalability, and monitoring in production environments

- Collaborate with cross-functional teams (product, data engineering, business stakeholders)

- Maintain best practices in MLOps, model versioning, and CI/CD pipelines

Required Skills & Qualifications :

Core ML & Data Science :

- Strong foundation in machine learning algorithms (supervised & unsupervised)

- Experience with anomaly detection, time-series, and predictive modeling

- Proficiency in Python and ML libraries (Scikit-learn, XGBoost, PyTorch/TensorFlow)

- Experience with data preprocessing, feature engineering, and model evaluation

Generative AI & NLP :

- Hands-on experience with LLMs (OpenAI, Claude, Hugging Face, etc.)

- Strong understanding of :

1. RAG (Retrieval-Augmented Generation)

2. Prompt engineering & evaluation

3. Embeddings & vector databases (e.g., FAISS, Milvus)

- Experience building GenAI applications (chatbots, document, summarization systems)

- Experience working with large datasets (batch + streaming)

- Knowledge of data pipelines and tools (Spark, Airflow, or similar)

- Familiarity with cloud platforms (Azure, AWS, or GCP)MLOps & Deployment

- Experience deploying models using APIs (FastAPI/Flask)

- Understanding of Docker, CI/CD pipelines, and model monitoring

- Knowledge of version control and experiment tracking tools

Preferred Qualifications :

- Experience in the Insurance domain (claims processing, fraud detection, underwriting analytics)

- Familiarity with document AI / OCR / NLP pipelines for insurance workflows

- Experience with graph-based or network-based anomaly detection

- Exposure to multi-agent systems or AI orchestration frameworks

- Understanding of regulatory and compliance considerations in insurance AI

Key Use Cases You Will Work On :

- AI-powered claims anomaly & fraud detection systems

- Intelligent document processing and insights extraction

- Generative AI-based assistants for claims and underwriting teams

- Predictive models for risk assessment and customer insights

Soft Skills :

- Strong problem-solving and analytical thinking

- Ability to work in a fast-paced, ambiguous environment

- Effective communication with both technical and business stakeholders

- Ownership mindset with a focus on delivering production-ready solutions

Nice to Have :

- Experience with LangChain / LlamaIndex / Semantic Kernel

- Knowledge of knowledge graphs and hybrid search systems

- Prior experience in enterprise AI solution development