Senior Software Engineer - Artificial Intelligence

Mandatory Skill Set

1. Python :

a. Develop, test, and maintain software applications using Python.

b. Write clean, maintainable, and efficient code following best practices and coding standards.

c. Exposure to version control systems such as Git/Gerrit

d. Familiarity with agile development methodologies.

2. Knowledge of Cloud

a. Certified as a cloud engineer on at least one major cloud platform ( Azure, AWS, GCP)

b. Experience in libraries such as TensorFlow, PyTorch, scikit-learn, and MLflow.

c. model training, model testing,

3. Machine Learning and MLOPs

a. Experience in libraries such as TensorFlow, PyTorch, scikit-learn, and MLflow.

b. Experience with MLOps: Proficiency in MLOps tools and frameworks, including Kubernetes, Docker, Jenkins, and CI/CD pipelines. Familiarity with deploying models on any one platform (AWS, GCP, or Azure.)

4. Data Science

a. Experience with EDA and ability to analyze complex data sets to identify trends, patterns, and insights that drive business decisions.

b. Have a strong understanding of feature engineering, model training, model testing, feature stores

c. Experience with data visualization tools such as Tableau, Power BI, or similar.

5. Generative AI

a. Hands on experience in developing basic applications using popular Generative AI models like Open AI GPT, Gemini, Llama, Bedrock etc.

b. Hands on experience in developing RAG based solutions using frameworks like LangChain

c. Experience in setting up vector databases. (Experience with knowledge graphs is highly desired)

6. Databases and Data Engineering

a. Familiarity with databases and data engineering concepts.

b. Working knowledge of SQL and RDBMS

Desired Skills:

1. Python:

a. Proficient in using Python libraries such as NumPy and Pandas for data manipulation and analysis.

b. Proficiency with Flask and Django for developing web applications and REST APIs.

c. Familiarity with libraries such as BeautifulSoup and Scrapy for web scraping.

d. Understanding of Matplotlib, Seaborn, and Plotly for data visualization.

2.Knowledge of Cloud :

a. Hands on familiarity with any one cloud based ML platforms (Azure ML Studio, Sagemaker, Vertex AI)

3.Machine Learning and MLOPS

a. Experience with cognitive ai frameworks (computer vision, NLP, conversational ai)

b. Must be familiar with ideas of responsible/ethical ai and ways of implementing these concepts into a solution.

c. Experience with Explainable AI frameworks.

4.Data Sceince

c. Experience with data visualization tools such as Tableau, Power BI, or similar.

5.Generative AI

a. Familiarity with generative AI and advanced neural network architectures.

b. Familiarity with concepts around Agentic workflow design