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 ourcustomers’ 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.

Position Details

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).