
AIML Practice Head
3 weeks ago
Experience: 15+ Years
Notice: Immedaite- 15 Days
About SIDGS:
SIDGS is a premium global systems integrator and global implementation partner of Google corporation, providing Digital Solutions & Services to Fortune 500 companies. Our Digital solutions go across following domains: User Experience, CMS, API Management, Microservices, DevOps, Cloud, Service Mesh, Artificial Intelligence, RPA domains.
We create innovative solutions in Digital, API Management, Cloud and DevOps space in partnership with Google. We understand that every business has a unique set of challenges and opportunities, and we leverage our unique industry insights, honed through decades of combined experience in the technology sector, to deliver the products, solutions, and services necessary to achieve best customer satisfaction and delivering positive impact to the communities.
Job Overview:
We are seeking a seasoned AIML practice headwho combines deep hands-on expertise in Python and machine learning with strong pre-sales solutioning skills. This role requires an architect who can engage clients, design scalable AI/ML solutions, and also lead or contribute to technical implementation.
Key Responsibilities:
AI/ML Architecture & Hands-on Delivery
- Design and implement end-to-end machine learning systems (data ingestion, feature engineering, model development, deployment, monitoring).
- Write clean, production-grade Python code for ML pipelines, APIs, and utilities.
- Develop and fine-tune models using Scikit-learn, TensorFlow, PyTorch, or Hugging Face.
- Design solutions for GenAI, NLP, computer vision, and recommendation systems.
Pre-Sales & Solution Engineering
- Collaborate with sales and business teams to understand client needs and propose ML/AI solutions.
- Lead technical discovery, client workshops, and PoC scoping sessions.
- Respond to RFPs/RFIs with solution architecture, estimation, and tech write-ups.
- Prepare and deliver engaging demos and technical presentations to CXOs and IT leaders.
Cloud & MLOps Integration
- Architect solutions using GCP (Vertex AI), AWS (SageMaker), or Azure (ML Studio).
- Deploy ML models using Docker, Kubernetes, FastAPI, or Flask.
- Implement MLOps workflows: model versioning, CI/CD pipelines, monitoring, and retraining.
Leadership & Collaboration
- Provide mentorship and technical guidance to junior data scientists and engineers.
- Stay current with advancements in AI/ML, GenAI, and tooling.
- Support delivery teams during project execution as a solution overseer or active contributor.
Required Skills:
Machine Learning & AI
- Strong grounding in ML fundamentals, supervised/unsupervised learning, and deep learning.
- Practical experience with NLP, GenAI (e.g., LLMs, RAG), time series, or image processing.
Programming (Python-first)
- Expert in Python for data science and backend integration.
- Familiar with Jupyter, Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow, Hugging Face.
- Experience building APIs with FastAPI/Flask and integrating ML into applications.
Cloud & MLOps
- Hands-on experience with any of: GCP Vertex AI, AWS SageMaker, or Azure ML.
- MLOps tools: MLflow, Kubeflow, Airflow, GitHub Actions, Docker, Kubernetes.
Pre-Sales & Client Engagement
- Experience leading technical discovery, PoCs, RFP responses, and stakeholder presentations.
- Ability to translate business problems into AI/ML solutions and articulate ROI.
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