AI/ML Engineer at Abstrabit Technologies Pvt Ltd

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

16 Mar, 26

Salary

0.0

Posted On

16 Dec, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, AI Solutions, Chatbots, Knowledge Management, Generative AI, NLP, Computer Vision, Python, TensorFlow, PyTorch, Keras, Data Science, Problem Solving, Communication, Analytical Skills, Deep Learning

Industry

Software Development

Description

Company Description We specialize in building intelligent AI agents that transform the way businesses operate. Our focus is on designing AI-driven solutions tailored to real-world use cases across industries – from customer engagement and sales automation to knowledge management and workflow optimization. Beyond AI agents, we offer end-to-end expertise in developing custom chatbots, scalable knowledge bases, and integrating advanced AI/ML capabilities into existing platforms. With innovation at the core, we are committed to helping businesses unlock efficiency, scale with intelligence, and deliver exceptional user experiences powered by the latest advancements in AI. Job Description Are you passionate about designing, building, and deploying intelligent systems that deliver real value? Abstrabit is seeking a motivated and skilled AI/ML Engineer to join our growing team at our Bengaluru office. In this role, you will be instrumental in developing and implementing sophisticated AI/ML solutions for our diverse clients. You'll work on projects involving custom chatbots, knowledge management, generative AI, and the integration of ML models into full-stack applications. This is a fantastic opportunity for engineers with foundational experience (0-3 years) to apply their skills to challenging problems and grow within a dynamic AI consulting environment. Responsibilities: Design & Develop: Design, develop, train, and deploy machine learning models and AI solutions, including custom chatbots and knowledge-based systems. Integrate Solutions: Integrate state-of-the-art AI/ML models (NLP, Computer Vision, Generative AI, etc.) into client products and internal platforms. Build & Optimize: Build, manage, and continuously improve knowledge bases that power intelligent applications. GenAI Implementation: Develop, fine-tune, and evaluate generative AI models and functionalities for various applications. Full-Stack Contribution: Contribute to the development of full-stack applications by implementing and embedding core AI/ML features. Test & Validate: Develop testing protocols, perform rigorous debugging, and ensure the performance, scalability, and reliability of AI/ML models and applications. Research & Innovate: Stay current with the latest advancements in AI/ML research, tools, and techniques, evaluating their potential and applying them to solve business challenges. Collaborate: Work closely with consultants, software developers, and clients to understand requirements, define solutions, and deliver impactful results. Agentic AI Expertise: Proven experience in building and deploying agentic AI systems (e.g., autonomous AI agents, multi-agent frameworks, workflow orchestration) using frameworks such as LangChain, LlamaIndex, n8n, Retell, Vapi, or Vector Databases, with a focus on real-world applications and problem-solving. Generative AI Expertise: Hands-on experience in developing, fine-tuning, and deploying generative AI models (LLMs, diffusion models, transformers) using frameworks like Hugging Face, OpenAI APIs, Stable Diffusion, or similar, with demonstrable projects in text, image, or multimodal generation. Qualifications Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a closely related quantitative field. Experience: 0-3 years of professional hands-on experience in building and deploying AI/ML models and solutions. ML Fundamentals: Strong theoretical understanding and practical experience with core machine learning algorithms (supervised, unsupervised learning), deep learning concepts, and potentially NLP or computer vision. Programming: Proficiency in Python is essential, along with strong experience using relevant data science and ML libraries (e.g., Pandas, NumPy, Scikit-learn). ML Frameworks: Hands-on experience with major ML/DL frameworks such as TensorFlow, PyTorch, or Keras. Problem Solving: Excellent analytical and problem-solving skills with meticulous attention to detail. Communication: Strong verbal and written communication skills, with the ability to explain complex concepts clearly.

Responsibilities

The AI/ML Engineer will design, develop, train, and deploy machine learning models and AI solutions, including custom chatbots and knowledge-based systems. They will also integrate AI/ML models into client products and contribute to full-stack applications.