AI/ML Engineer

As an AI/ML Engineer, you will research and select the right ML/LLM models and turn them into working integrations for our products and our customers’ systems (SaaS, portals, e‑commerce, CRM/ERP, mobile apps, internal tools). You will own end‑to‑end delivery: from understanding the business problem to building workflows (e.g., n8n/Make) and deploying and maintaining AI features in production.

This is a hands‑on engineering role: you should enjoy building and deploying real AI features and integrations more than only doing analytical research or dashboards.

Position: AI/ML Engineer

Number of Positions: Two

Experience: Open to all levels (from strong fresher to experienced)

Location: Surat, Gujarat (INDIA)

Roles & Responsibilities:

Research and evaluate ML/LLM and Vision models that can improve our internal operations and our customers’ business processes (SaaS, portals, e‑commerce, CRM/ERP, mobile apps).
Evaluate, develop, optimize, use and self‑host models needed for various jobs.
Design and build AI integrations for CRM, ERP, inventory, and other business systems, including Model Context Protocol (MCP) ‑ based integrations where relevant.
Implement AI‑driven workflows using tools like n8n, Make, Zapier, etc., and connect them with APIs, databases, and third‑party services.
Build Vision ML pipelines for video feeds and images (face/object detection, matching, analytics, quality checks, etc.).
Develop search and e‑commerce features using LLMs and retrieval (Apache Solr, Elasticsearch, vector search) and connect them to front‑end apps and back‑office tools.
Create WhatsApp and multi‑channel automations powered by LLMs and other AI models.
Monitor, debug, and improve AI workflows and integrations running in production environments.

Required Skills:

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related field.
Hands‑on experience in building and deploying machine learning or LLM‑based features in real applications (internships, projects, or production experience).
Strong programming skills in Python and experience with deep learning and ML frameworks such as TensorFlow and/or PyTorch, plus common data science libraries (NumPy, pandas, scikit‑learn, etc.).
Strong experience working with REST APIs, webhooks, and integrating third‑party systems (CRM/ERP/Inventory/WhatsApp/etc.).
Hands‑on experience building automations with tools like n8n, Make, or similar low/no‑code workflow platforms.
Comfort deploying models and services (Docker, cloud, simple MLOps) and wiring them into existing products.
Solid understanding of natural language processing (NLP) and deep learning techniques, including working with LLMs and transformer-based architectures.
Practical experience with LLM APIs (e.g., OpenAI, Gemini, etc.) for building real applications and workflows.
Knowledge of data engineering concepts: data preprocessing, ETL/ELT pipelines, data quality, and working with relational and NoSQL databases.
Familiarity with retrieval and search technologies (e.g., Apache Solr, Elasticsearch, vector search / vector databases) is a strong plus.
Exposure to Vision ML (image/video processing, classical CV and/or deep learning‑based CV) is a plus; strong interest here is also valued.
Familiarity with cloud platforms (AWS, Azure, GCP) and deploying ML models or data pipelines in cloud environments.
Strong research mindset, problem‑solving skills, and ability to design experiments, interpret results, and iterate.
Excellent communication and collaboration skills, comfortable working in cross‑functional product and client teams.

Nice-to-have / Bonus:

Experience building AI features specifically for e‑commerce (search, recommendation, personalization, chatbot, fraud/risk scoring, review analysis) or SaaS products (copilots, analytics insights, smart workflows)
Experience with MLOps tools and practices (model versioning, CI/CD for ML, monitoring, observability).
Prior work in a consulting, services, or staff augmentation context, managing multiple projects or stakeholders.
Please include 2–3 concrete examples (links or brief descriptions) of AI/LLM or automation projects you have built or contributed to (e.g., GitHub repos, demos, case studies, Kaggle, hackathons).

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AI/ML Engineer

Roles & Responsibilities:

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