Teamware Solutions
Website:
teamwaresolutions.net
Job details:
Roles & responsibilities
Model Development & Solution Architecture
🔹Design, build, and optimize machine learning, GenAI, and statistical models to solve complex cross‑domain business challenges.
🔹Develop reproducible, scalable workflows using modern MLOps practices; conduct rigorous model evaluation and continuous improvement for accuracy, reliability, and fairness.
Architect end‑to‑end AI systems including data pipelines, vector databases, orchestration layers, and deployment frameworks.
GenAI, RAG & Agentic Systems
🔹Explore and implement advanced LLM techniques, including embeddings, retrieval‑augmented generation (RAG), agentic workflows, tool use, memory, and multimodal reasoning.
🔹Build production‑grade GenAI applications using LangChain, LangGraph, and ecosystem tools for orchestration, evaluation, and deployment.
🔹Experiment with foundation models across open‑source and commercial platforms to identify best‑fit models for business use cases.
API & Integration Development
🔹Develop and operationalize scalable APIs—preferably with FastAPI (Python)—to integrate ML/GenAI components with enterprise systems, SaaS products, and data platforms.
🔹Collaborate on deployment patterns including microservices, serverless, and containerized workloads (Docker/Kubernetes).
Cloud Platforms & Infrastructure
🔹Architect and deploy AI solutions on Azure, Google Cloud Platform (GCP), or AWS, leveraging managed AI/ML services (Azure ML, Vertex AI, SageMaker), vector search, and serverless compute.
🔹Ensure security, scalability, compliance, and monitoring in all cloud‑based AI deployments.
Consulting, Problem Solving & Stakeholder Collaboration
🔹Partner with product teams, business stakeholders, SMEs, and engineering groups to deeply understand challenges, run discovery workshops, and shape AI strategy and roadmaps.
🔹Translate business requirements into scalable technical architectures, solution designs, and implementation plans.
🔹Communicate complex AI concepts in clear, business‑friendly language and drive adoption of AI‑powered solutions across the organization.
Certification: Certification in cloud technologies especially Azure open AI would be good to have
Work experience
🔹2-5 years of work experience in data science or related field
🔹Hands on experience in Python and R
Mandatory technical & functional skills
Programming skills:
🔹Proficiency in programming languages such as Python and R, and experience with data manipulation libraries (e.g., pandas, NumPy) and machine learning frameworks (e.g., TensorFlow).
Statistical knowledge:
🔹Strong understanding of statistical concepts and methodologies such as regression, clustering, hypothesis testing, and time series analysis.
GenAI-based models:
🔹Understanding and experience with GenAI-based models, exploring their potential applications, and incorporating them into AI models when appropriate
Communication skills:
🔹Strong written and verbal communication skills to effectively present findings, insights, and recommendations to both technical and non-technical stakeholders.
Team player:
🔹Proven ability to collaborate effectively with cross-functional teams, take ownership of tasks, and work towards shared goals.
AI passion:
🔹Demonstrated interest and enthusiasm for artificial intelligence and a strong desire to grow a career in the AI space
Problem-solving mindset:
🔹Ability to think critically and creatively to solve complex business problems using data-driven approaches. Detail-oriented with excellent analytical and problem-solving skills.
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