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Lead AI ML Engineer @ Cirruslabs

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 Lead AI ML Engineer

Job Description

Role & responsibilities


Mandatory skills: Python, Gen AI, traditional ML, core Data scientist

Position Overview
We are seeking an experienced Senior Full Stack AI/ML Engineer to join our dynamic team. This role combines deep technical expertise in traditional statistics, classical machine learning, and modern AI with full-stack development capabilities to build end-to-end intelligent systems. You'll work on revolutionary projects involving generative AI, large language models, and advanced data science applications.
Key Responsibilities
AI/ML Development & Data Science:

  • Design, develop, and deploy machine learning models ranging from classical algorithms to deep learning for production environments
  • Apply traditional statistical methods including hypothesis testing, regression analysis, time series forecasting, and experimental design
  • Build and optimize large language model applications including fine-tuning, prompt engineering, and model evaluation
  • Implement Retrieval Augmented Generation (RAG) systems for enhanced AI capabilities
  • Conduct advanced data analysis, statistical modeling, A/B testing, and predictive analytics using both classical and modern techniques
  • Research and prototype cutting-edge generative AI solutions

Traditional ML & Statistics:

  • Implement classical machine learning algorithms including linear/logistic regression, decision trees, random forests, SVM, clustering, and ensemble methods
  • Perform feature engineering, selection, and dimensionality reduction techniques
  • Conduct statistical inference, confidence intervals, and significance testing
  • Design and analyze controlled experiments and observational studies
  • Apply Bayesian methods and probabilistic modeling approaches

Full Stack Development:

  • Develop scalable front-end applications using modern frameworks (React, Vue.js, Angular)
  • Build robust backend services and APIs using Python, Node.js, or similar technologies
  • Design and implement database solutions (SQL/NoSQL) optimized for ML workloads
  • Create intuitive user interfaces for AI-powered applications and statistical dashboards

MLOps & Infrastructure:

  • Establish and maintain ML pipelines for model training, validation, and deployment
  • Implement CI/CD workflows for ML models using tools like MLflow, Kubeflow, or similar
  • Monitor model performance, drift detection, and automated retraining systems
  • Deploy and scale ML solutions using cloud platforms (AWS, GCP, Azure)
  • Containerize applications using Docker and orchestrate with Kubernetes

Collaboration & Leadership:

  • Work closely with data scientists, product managers, and engineering teams
  • Mentor junior engineers and contribute to technical decision-making
  • Participate in code reviews and maintain high development standards
  • Stay current with latest AI/ML trends and technologies

Required Qualifications
Experience & Education:

  • 7-8 years of professional software development experience
  • Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Machine Learning, Data Science, or related field
  • 6+ years of hands-on AI/ML experience in production environments

Technical Skills:

  • Programming: Expert proficiency in Python, strong experience with JavaScript/TypeScript, R is a plus
  • Traditional ML: Scikit-learn, XGBoost, LightGBM, classical algorithms and ensemble methods
  • Statistics: Hypothesis testing, regression analysis, ANOVA, time series analysis, experimental design, Bayesian inference
  • Statistical Tools: Experience with R, SAS, SPSS, or similar statistical software packages
  • Deep Learning: TensorFlow, PyTorch, neural networks, computer vision, NLP
  • LLM Experience: Working with GPT, Claude, Llama, or similar models; experience with fine-tuning and prompt engineering
  • RAG Implementation: Vector databases (Pinecone, Weaviate, Chroma), embedding models, semantic search
  • Data Science: Pandas, NumPy, statistical analysis, data visualization (Matplotlib, Plotly, Seaborn), feature engineering
  • Full Stack: React/Vue.js, Node.js/FastAPI, REST/GraphQL APIs
  • Databases: PostgreSQL, MongoDB, Redis, vector databases
  • MLOps: Docker, Kubernetes, CI/CD, model versioning, monitoring tools
  • Cloud Platforms: AWS/GCP/Azure, serverless architectures

Soft Skills:

  • Strong problem-solving and analytical thinking
  • Excellent communication and collaboration abilities
  • Self-motivated with ability to work in fast-paced environments
  • Experience with agile development methodologies

Preferred Qualifications

  • Experience with causal inference methods and econometric techniques
  • Knowledge of distributed computing frameworks (Spark, Dask)
  • Experience with edge AI and model optimization techniques
  • Publications in AI/ML/Statistics conferences or journals
  • Open source contributions to ML/statistical projects
  • Experience with advanced statistical modeling and multivariate analysis
  • Familiarity with operations research and optimization techniques

Job Classification

Industry: IT Services & Consulting
Functional Area / Department: Data Science & Analytics
Role Category: Data Science & Machine Learning
Role: Full Stack Data Scientist
Employement Type: Full time

Contact Details:

Company: Cirruslabs
Location(s): Bengaluru

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Keyskills:   Generative Ai Machine Learning Python Data Science Artificial Intelligence

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Cirruslabs

We are CirrusLabs. Our vision is to become the world's most sought-after niche digital transformation company that helps customers realize value through innovation. Our mission is to co-create success with our customers, partners and community. Our goal is to enable employees to dream, grow and make...