Develop and deploy advanced Generative AI large language models, Machine Learning and Deep Learning models/algorithms to enhance or automate business processes with predictive decision-making, content aggregation, and contextual insights
Collaborate with data scientists and data engineers to build production-level models and pipelines, including dataset preprocessing and model output postprocessing
Process, cleanse, and verify integrity of structured and unstructured business data used in analysis
Analyze large data sets to uncover trends and patterns for solving business problems; perform feature selection and data transformation for model optimization
Evaluate, visualize, and communicate AI/ML model results and their correlation with business KPIs
Operate in a startup-type environment to design and build innovative apps using automation, cognitive services, and ML from PoC to production-ready solutions
Lead assessments, workshops, and detailed analysis to recommend AI-driven solutions with high business impact
Work within project planning constraints; identify project risks/issues and communicate effectively with delivery managers
Support operations teams during UAT and go-live, and develop standard operational practices
Continuously optimize existing AI/ML operations, build monitoring and alerting systems for early issue detection
Partner with business users, functional teams, and stakeholders to translate business problems into technical solutions
You Must Have:
Bachelor's in Computer Science, Data Science, or Engineering fields
4–6 years of IT experience in solution architecture, data science, or software development
Hands-on experience with LLM engineering and LLMOps, including advanced prompt engineering and fine-tuning of LLMs
3+ years experience in building/deploying ML solutions using supervised and unsupervised algorithms (e.g., Linear/Logistic Regression, SVMs, DNNs, Random Forest)
3+ years hands-on experience with Python and ML libraries like scikit-learn, Keras, TensorFlow
2+ years experience with NLP/NLG frameworks (e.g., HuggingFace, NLTK, Spacy, Gensim)
2+ years experience on Databricks platform
2+ years experience developing AI/ML cognitive services on Azure Cloud and Databricks
We Value:
Master's Degree in Computer Science, Data Science, or Engineering
Educational or work experience in data science, data engineering, and analytics
Proficiency in feature engineering, model tuning, and algorithm selection
Familiarity with frameworks such as LangChain, LlamaIndex, and vector databases
Experience with NLP/NLG, AI Chatbots, and OCR technologies
Experience with Big Data technologies (e.g., Hadoop, PySpark, Hive)
Familiarity with DevSecOps, CI/CD pipelines, and workflow orchestration tools (e.g., Airflow, Opsera)
Experience with Docker and Kubernetes
Prior work in Agile/Scrum/SAFe and DevOps environments
Relevant certifications or coursework in Generative AI, AI/ML, and Cloud platforms
