Mp Stack engineer Jobs – 139 Open Jobs Today

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Senior AI/ML Lead
Synsoft Global —Indore, Madhya Pradesh
If you’re seeking technical autonomy, client-facing impact, and team-building ownership, this is your place. 5+ years of experience as an AI/ML Engineer.
Director/Principal
Gyan Ganga Group, Jabalpur —Jabalpur, Madhya Pradesh
Build strategic partnerships with industry, academia, government, and international institutions. Strengthen industry relations, placements, and corporate…
₹50,000 - ₹3,50,000 a month
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stack engineer jobs near mp

Full-time, On-site Role
5+ years of experience as an AI/ML Engineer
Atleast 2+ years in a leadership or team-building role
Experience in building powerful, real-world applications across various domains
Strong communication skills and the ability to explain complex AI concepts to business stakeholders and clients.
Experience in leading small to mid-sized teams.
A product-first mindset and the ability to drive initiatives from idea to production.
Passion for staying at the cutting edge of AI — especially in the era of LLMs and generative AI.
Work in a collaborative, high-ownership, fast-moving tech environment
You’ll be setting up the AI engine for a company already trusted for its tech excellence.
If you’re seeking technical autonomy, client-facing impact, and team-building ownership, this is your place.

Lead the design, development, and deployment of AI/ML and Deep Learning models.
Hire, train, and mentor a growing team of AI/ML engineers and data scientists.
Own the architecture and tech stack decisions for the AI division.
Engage in client discovery calls and pre-sales conversations to convert technical insights into business opportunities.
Lead PoC development, client interviews, and project planning in collaboration with internal and external stakeholders.
Stay updated with the latest in AI/ML (especially LLMs, vector search, generative AI, multi-agent chatbot) and translate advancements into real-world implementations.

Bachelor’s or Master’s degree in CS/IT / AI-ML / Data Science
Python, NumPy, Pandas, Scikit-learn, PySpark
Deep Learning: TensorFlow, PyTorch, Keras
CNNs, RNNs, Attention Mechanisms, Transformers
SVD (Singular Value Decomposition), KMeans, Recency weight
Text embeddings, semantic search, vector DBs (FAISS, Pinecone, Weaviate)
Model Context Protocol (MCP)
Model Lifecycle: Data preprocessing, training, tuning, evaluation (ROC, F1, AUC, confusion matrix)
Botpress / Copilot Studio workflow and integration experience
Deployment: RESTful ML APIs, Docker, AWS/GCP (SageMaker, Vertex AI), model versioning
Workflow Tools: MLflow, Azure ML, Airflow, Git-based CI/CD
Creating REST APIs using FastAPI framework or equivalent