Analytics Solutions Associate

Make a real impact by solving complex problems and delivering cutting-edge models into production environments. Collaborate with experts to design and deploy advanced solutions that drive quality and productivity.

Job Summary:

As an Applied AI/ML Engineer/Data Scientist within our team, you will be responsible for developing and implementing AI/ML solutions to improve quality and productivity in Software Testing, SRE problems, and solve complex Technology Operations. You will work closely with cross-functional teams to understand requirements, design and develop AI/ML models, and deploy them into UAT/production.

Job Responsibilities:

- Develop and implement AI/ML models and algorithms to solve business problems.

- Collaborate with cross-functional teams to understand requirements and translate them into technical solutions.

- Train and evaluate AI/ML models using large datasets.

- Train and evaluate AI/ML models to help design test cases , automate coding , design self healing codes , predict defects, identify optimized regression cases, etc.

- Apply advanced statistical and ML techniques, including predictive modeling, time series analysis, and optimization algorithms, to extract insights from complex data sets.

- Optimize and fine-tune AI/ML models for performance and accuracy.

- Design and develop data pipelines to preprocess and transform data for AI/ML models.

- Stay updated with the latest trends and advancements in data science, machine learning, and related fields, and actively seek opportunities to enhance skills and knowledge.

Required qualifications, capabilities, and skills

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

- Minimum 6 years of demonstrated experience in applied AI/ML engineering.

- Strong programming skills in Python, with experience in developing and maintaining production-level code.

- Proficiency in working with large datasets and data preprocessing.

-Solid understanding of Software Testing and SRE practices

- Solid understanding of AI/ML algorithms and techniques, including deep learning, time series forecasting and natural language processing.

- Experience in Agentic AI

- Experience with cloud platforms, such as AWS for deploying and scaling AI/ML models.

- Strong problem-solving and analytical skills.

- Excellent communication and collaboration skills.

- Knowledge of infrastructure operations

Preferred qualifications, capabilities, and skills

- Experience in backend development, including databases (SQL/NoSQL/Graph), programming languages (Python/Java/Node.js), web frameworks, APIs, and microservices and possess front-end development skills, including HTML, CSS, and JavaScript

- Experience in Automated software testing and Test Automation Frameworks

- Knowledge of large language models (LLMs) , Generative AI and accompanying toolsets the LLM ecosystem (e.g. Langchain, Vector databases, CHATGPT)

- Assess and choose suitable LLM tools and models for diverse tasks including but not limited to curating custom datasets and fine-tune LLM with a focus on parameter-efficient, mixture-of-expert, and instruction methods designing and developing advanced LLM prompts, Retrieval-Augmented Generation (RAG) solutions, and Intelligent agents for the LLMs and executing experiments to push the capability limits of LLM models and enhance their dependability.