Infosys is seeking a Data Scientist / Gen AI Lead Consultant with ZGenerative AI, Agentic AI, Machine Learning (ML), AI and Python experience. Ideal candidate is expected to have prior experience in end-to-end implementation of Gen AI and Agentic AI based solution, fine tuning large language models, Machine Learning models that includes identification of 'right' problem, designing 'optimum' solution, implementing using 'best in class' practices and deploying the models to production. Will work in alignment with data strategy at various clients, using multiple technologies and platforms.

Required Qualifications:

• Bachelor's Degree or foreign equivalent will also consider three years of progressive experience in the specialty in lieu of every year of education.

• At least 7 years of Information Technology experience

• At least 4 years of hands-on GenAI / Agentic AI and data science with machine learning

• Strong proficiency in Python programming.

• Experience of deploying the Gen AI applications with one of the Agent Frameworks like Langgraph, Autogen, Crew AI.

• Experience in deploying the Gen AI stack/services provided by various platforms such as AWS, GCP, Azure, IBM Watson

• Experience in Generative AI and working with multiple Large Language Models and implementing Advanced RAG based solutions.

• Experience in processing/ingesting unstructured data from PDFs, HTML, Image files, audio to text etc.

• Experience with data gathering, data quality, system architecture, coding best practices

• Hands-on experience with Vector Databases (such as FAISS, Pinecone, Weaviate, or Azure AI Search).

• Experience with Lean / Agile development methodologies

• This position may require travel, will involve close co-ordination with offshore teams

• This position is located in Bridgewater, NJ; Sunnyvale, CA; Austin, TX; Raleigh, NC; Richardson, TX; Tempe, AZ; Phoenix, AZ; Charlotte, NC; Houston, TX; Denver, CO; Hartford, CT; New York, NY, Palm Beach, FL; Tampa, FL or Alpharetta, GA, or is willing to relocate.

• Candidates authorized to work for any employer in the United States without employer-based visa sponsorship are welcome to apply. Infosys is unable to provide immigration sponsorship for this role at this time

Preferred Data Scientist Qualifications:

• 4 years of hands-on experience with more than one programming language; Python, R, Scala, Java, SQL

• Hands-on experience with CI/CD pipelines and DevOps tools like Jenkins, GitHub Actions, or Terraform.

• Proficiency in NoSQL and SQL databases (PostgreSQL, MongoDB, CosmosDB, DynamoDB).

• Deep Learning experience with CNNs, RNN, LSTMs and the latest research trends

• Experience in Python AI/ML frameworks such as Tensor Flow, Py Torch, or Lang Chain.

• Strong understanding and experience of LLM fine-tuning, local deployment of open-source models

• Proficiency in building RESTful APIs using FastAPI, Flask, or Django.

• Experience in Model evaluation tools like Deep Eval, FMeval, RAGAS , Bedrock model evaluation.

• Experience with perception (e.g. computer vision), time series data (e.g. text analysis)

• Big Data Experience strongly preferred, HDFS, Hive, Spark, Scala

• Data visualization tools such as Tableau, Query languages such as SQL, Hive

• Good applied statistics skills, such as distributions, statistical testing, regression, etc.

The job entails sitting as well as working at a computer for extended periods of time. Should be able to communicate by telephone, email or face to face. Travel may be required as per the job requirements.

The estimated annual compensation range for candidates in the below locations will be-
Sunnyvale, CA; Bridgewater, NJ; New York, NY, Denver, CO: $94000 to $164500

Along with competitive pay, as a full-time Infosys employee, you are also eligible for the following benefits :

• Medical/Dental/Vision/Life Insurance

• Long-term/Short-term Disability

• Health and Dependent Care Reimbursement Accounts

• Insurance (Accident, Critical Illness, Hospital Indemnity, Legal)

• 401(k) plan and contributions dependent on salary level

• Paid holidays plus Paid Time Off