AI/ML Engineer

Company Description

VentraGate is a Cloud-focused solutions and services firm specializing in driving digital transformation and developing cloud-based technologies that users love to interact with. As a leading transformation consultancy, VentraGate partners with businesses of all sizes to foster innovation, enhance agility, and maintain competitiveness. The company is dedicated to helping organizations embrace cutting-edge technologies to achieve their strategic goals effectively.

Key Responsibilities

● Design, develop, and deploy Al/ML models with a strong focus on Generative Al (LLMs, diffusion models, multimodal Al). ● Build, fine-tune, and evaluate large language models for domain-specific applications. ● Develop agentic Al systems (autonomous/assistive agents) capable of reasoning, planning, and tool use. ● Integrate AI/ML models into production systems, APIs, and applications. ● Conduct experiments, benchmark models, and optimize for scalability, efficiency, and cost. ● Write clean, modular, and well-documented code for ML pipelines and Al services. ● Implement best practices for model monitoring, observability, and troubleshooting in production. ● Contribute to research exploration, technical discussions, and knowledge sharing within the Al/ML team.

What We're Looking For

● 1-2 years of experience as an Al/ML Engineer. ● Strong hands-on expertise with Python and popular ML/Al frameworks (PyTorch, TensorFlow, Hugging Face). ● Solid understanding of Generative Al concepts (LLMs, embeddings, prompt engineering, RAG). ● Familiarity with agentic Al frameworks (LangChain, Llamalndex, Haystack, AutoGen, etc.). ● Experience in building, fine-tuning, or deploying transformer-based models. ● Knowledge of vector databases (Pinecone, Weaviate, FAISS, Milvus). ● Understanding of cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes). ● Strong foundation in data structures, algorithms, and ML fundamentals. ● Excellent problem-solving, debugging, and communication skills. Nice to Have ● Experience with reinforcement learning, multi-agent systems, or Al reasoning frameworks. ● Knowledge of MLOps tools (MLflow, Weights & Biases, Kubeflow). ● Exposure to multimodal Al (text, image, audio, video)