Machine Learning Specialist

Bachelor's Degree in Information Technology or Computer Science or Engineering or related course work

· 3-5 years of Experience working in Design, fine-tune, and deploy LLMs for enterprise use cases.

· Build agentic systems capable of autonomous decision-making and task execution.

· Integrate LLMs with legacy systems and modern cloud-native applications.

· Experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.

· Experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.

· Develop and optimize ML models for classification, prediction, and recommendation tasks.

· Contribute to front-end and back-end development using Node.js, Python. Work with AWS services for scalable deployment of AI/ML solutions.

· Design and manage SQL Server databases and data pipelines.

· Experience in working with GenAI, agentic frameworks like OpenAI API, LangChain, CrewAI.

· Work closely with cross-functional teams including architects, product owners, and business stakeholders.

· Strong knowledge of data structures, algorithms, and software engineering principles.

· Familiarity with cloud-based platforms and services, such as AWS, GCP, or Azure.

· Strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.

Required Experience & Education:

• Proven experience with design and development of large-scale enterprise application solutions.

• College degree (Bachelor) in related technical/business areas or equivalent work experience.

• 3-5 years of experience in Software engineering

• Hands-on experience engineering/developing modern on-prem/public AWS solutions, Python and LLM models.

• Willing to learn, go above and beyond attitudes.

• Experience with modern and legacy development languages.

Desired Experience:

• Healthcare experience is preferred.

Location & Hours of Work

• Full-time position, working 40 hours per week. Expected overlap with US hours as appropriate

• Primarily based in the Innovation Hub in Hyderabad, India in a hybrid working model (3 days WFO and 2 days WAH)