ML Engineer

Job Description

With excellent analytical and problem-solving skills, you should understand business problems of the customers, translate them into scope of work and technical specifications for developing into Data Science projects. Efficiently utilize cutting edge technologies in AI areas (Machine Learning, NLP, Computer Vision) and development of solutions for business problems. Good exposure technology platforms for Data Science, AI, Gen AI, cloud with implementation experience. Ability to understand data, requirements, design and develop a Machine Learning Model for the requirements. This Job requires the following:

Designing, developing, and implementing end-to-end machine learning production pipelines (data exploration, sampling, training data generation, feature engineering, model building, and performance evaluation)

Experience in predictive analytics and statistical modeling

Experience in successfully making use of the following: Logistic Regression Multivariate Regression, Support Vector Machines, Stochastic Processes, Decision Trees, Lifetime analysis, common clustering algorithms, Optimization, CNN

Essential Qualifications

B-Tech or BE - computer / IT or MCA or MSC- Computer Science along with necessary certifications is preferred

Technical Qualifications (Essential)

- Hands-on programming experience
- Hands-on technical design experience
- Hands-on prompt engineering experience
- Design and Development of at least 3 Data Science, AI Projects with design and development of Machine Learning models
- 1 Generative AI Project designed, developed and delivered to production is desirable

Primary Skills

- Hands-on coding experience in Python, PyTorch, Spark/PySpark, SQL, TensorFlow, NLP Frameworks and similar tools/frameworks
- Good understanding of business and domain of the applications
- Hands-on experience in design and development of Gen AI applications using Open Source LLMs and cloud platforms
- Hands-on experience in design and development of API based applications for AI and Data Science Projects
- Understanding in GenAI concepts, RAG and Models fine-tuning techniques is desirable
- Understand the concepts of major AI models such as OpenAI, Llama, Hugging Face, Mistral AI etc.,
- Understanding of DevOps pipelines for deployment
- Good understanding of Data Engineering lifecycle data pipelines, data warehouse, data lake

Secondary Skills

- Experience using Databricks and Azure Data platform
- Knowledge of any configuration management tools is desirable
- Familiarity with containerization and container orchestration services like Docker and Kubernetes

Experience

Description of Responsibility

- Understand customer s requirements (Business, Functional, Non-Functional etc.,), design and develop Machine Learning Models
- Design and implement Machine Learning Models using major technology and computing platforms (open source and cloud
- Possess excellent analytical and problem-solving skills and be able to understand various forms of data, patterns and derive insights.
- Collaborate internal and external stakeholders for deriving solution that requires cross functional teams and smoother execution of the projects
- Knowledge of data modeling and understanding of different data structures
- Experience with design of AI/ML solutions either as standalone or integrated with other applications
- Experience in Generative AI solutions for the business/automation requirements using open source LLMs (Open AI, LLama, Mistral etc.,) is desirable

Sills / Competencies requirement

- Research Orientation
- Proactive Clear Communication
- Collaboration
- Solution Orientation
- Solution Articulation
- Accountability
- Adaptability / Flexibility
- Analytical Skills
- Listening Skills
- Customer Service Orientation

---