Why This Role Stands Out
This hybrid AI/ML Engineer role at Mphasis offers a fantastic opportunity to innovate within cutting-edge Generative AI and Retrieval Augmented Generation solutions for software testing, with excellent potential for skills development in areas like LLMs and agentic AI. You'll thrive here if you're a mid-senior level professional with strong Python, software development, and AIML expertise, eager to contribute to impactful quality assurance advancements within a collaborative environment. Apply now to leverage your technical prowess and shape the future of AI-driven testing!
Quick Overview
Job Description
Job Title: AI/ML Engineer Designation: Data Scientist
Job Summary: We are seeking a skilled AI/ML Engineer with a strong foundation in Artificial Intelligence and Machine Learning (AIML) and software development. The ideal candidate will be proficient in Python and have hands-on experience with Generative AI and Retrieval Augmented Generation solutions, particularly in the context of software testing. This role requires a blend of technical expertise, innovative thinking, and effective communication skills to contribute to our quality assurance solutions.
Responsibilities:
- Develop and implement AIML solutions focused on enhancing software testing processes.
- Utilize Generative AI and Retrieval Augmented Generation techniques to improve testing efficiency and accuracy.
- Work with Large Language Models (e.g., GPT, Claude) to create and optimize AIML applications.
- Leverage GitHub Copilot for code generation and enhancement in AIML projects.
- Regularly utilize Agentic AI solutions and Model Control Platforms (MCPs) in project workflows.
- Deploy AIML solutions using Docker and Kubernetes, ensuring scalability and reliability.
- Collaborate with front-end developers to build user interfaces using React for AIML applications.
- Employ Python libraries such as NLTK, NumPy, Scikit-learn, and Pandas for data manipulation and model development.
- Implement AIML algorithms including Regression, Classification, Decision Trees, KNN, and K-Means.
- Build, train, and fine-tune AIML models to meet project requirements.
- Apply lifecycle principles and quality assurance methodologies throughout the development process.
- Conduct automated testing and maintain a strong understanding of test automation frameworks.
- Utilize SQL for data querying and management as part of AIML solutions.
- Participate in Agile processes, including sprint planning, backlog refinement, and retrospectives.
- Communicate effectively with both technical and business stakeholders to ensure alignment on project goals.
Mandatory Skills:
- Proficiency in AIML and Python programming.
- Experience with Generative AI and Retrieval Augmented Generation solutions.
- Hands-on experience with Large Language Models (GPT, Claude).
- Familiarity with GitHub Copilot.
- Regular user of Agentic AI solutions and MCPs.
- Deployment experience with Docker and Kubernetes.
- Strong knowledge of Python libraries (NLTK, NumPy, Scikit-learn, Pandas).
- Understanding of AIML algorithms (Regression, Classification, Decision Trees, KNN, K-Means).
- Experience with automated testing and test automation frameworks.
- Good grasp of SQL.
- Experience working in an Agile environment.
- Excellent verbal and written communication skills.
Preferred Skills:
- Experience in building, training, and fine-tuning AIML models.
- Front-end development experience using React.
Qualifications:
- Bachelor’s degree in Computer Science or a related field, or equivalent relevant experience.
- Demonstrated experience in Data Science and AIML with a focus on quality assurance solutions.
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