Lead AI ML Engineer
- Cirruslabs
- 6 - 11 years
- Bengaluru
- 9 months ago
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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 & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Full Stack Data ScientistEmployement Type: Full timeContact Details:
Company: CirruslabsLocation(s): Bengaluru
Keyskills: Generative Ai Machine Learning Python Data Science Artificial Intelligence
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