Maino.ai - ML Engineer (Data Scientist)

Reposted 14 Days Ago
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Bangalore, Bengaluru Urban, Karnataka, IND
In-Office
Senior level
Artificial Intelligence • HR Tech • Professional Services • Software
The Role
Design, fine-tune, and productionize LLM-based conversational and retrieval systems. Build scalable data pipelines and indexing, apply prompt engineering and few-shot learning, design APIs, run A/B tests and KPI monitoring, collaborate with engineering teams, and ensure data privacy, ethical AI, and secure, maintainable deployments.
Summary Generated by Built In

About Maino.ai

Maino.ai is at the forefront of revolutionising marketing automation through its end-to-end automated, intelligent, and ROI-driven martech platform. Leveraging cutting-edge Machine Learning (ML) and Generative AI technologies, we are committed to providing a one-stop solution that addresses all the marketing needs of organisations. Our mission is to build the world's most reliable and innovative technology platform, transforming the digital marketing sector into a cost-efficient and accessible domain for everyone.

Job Description:

At Maino.ai, we are seeking talented folks with 5+ years of experience in AI/ML with comprehensive understanding of the ML models ecosystem. This role offers a unique opportunity for someone passionate about pushing the boundaries of technology and thriving in a dynamic environment.

Qualifications:

Must-Have:

● Proficiency in Python and libraries like TensorFlow, PyTorch, Transformers, and LangChain.

● Solid understanding of NLP techniques, including tokenization, embeddings, and model fine-tuning.

● Hands-on experience with designing APIs and integrating AI models into production systems.

● Strong knowledge of machine learning fundamentals and evaluation metrics for conversational AI.

● Excellent problem-solving skills with a focus on delivering scalable and maintainable solutions.

● Strong experience with Large Language Models (LLMs) and frameworks such as OpenAI APIs, Hugging Face, or similar tools. (At least 1 year development experience)

Good-to-Have:

● Experience in deploying ML models in cloud environments (AWS, Azure, GCP).

● Exposure to tools like Docker, Kubernetes, or other container orchestration systems.

● Prior experience in developing multimodal conversational systems.

Responsibilities:

● Implement scalable data pipelines for processing and indexing large corpora of documents for retrieval systems.

● Research and apply advanced techniques in prompt engineering, few-shot learning, and knowledge integration to improve conversational and retrieval quality.

● Collaborate with other engineering teams.

● Conduct rigorous A/B testing, monitor key performance indicators (KPIs), and iteratively optimise system performance.

● Stay updated with the latest advancements in natural language processing (NLP) and machine learning to continuously innovate solutions.

● Ensure data privacy, ethical AI principles, and compliance with security standards in all models and systems.

Skills Required

  • 5+ years experience in AI/ML
  • Proficiency in Python
  • TensorFlow
  • PyTorch
  • Transformers library
  • LangChain
  • Strong experience with Large Language Models and frameworks (OpenAI API, Hugging Face, or similar) — at least 1 year development experience
  • Solid understanding of NLP techniques (tokenization, embeddings, model fine-tuning)
  • Hands-on experience designing APIs and integrating AI models into production systems
  • Strong knowledge of ML fundamentals and evaluation metrics for conversational AI
  • Excellent problem-solving skills focused on scalable, maintainable solutions
  • Experience deploying ML models in cloud environments (AWS, Azure, GCP)
  • Exposure to Docker, Kubernetes, or other container orchestration systems
  • Prior experience developing multimodal conversational systems
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The Company
100 Employees

What We Do

NextHire Consulting is an AI-driven recruiting platform that streamlines the hiring process for companies. By leveraging AI agents for sourcing, screening, and interviewing, the platform enables teams to focus on pre-qualified finalists. It provides data-driven insights into candidate soft skills and behavioral styles, aiming to disrupt traditional recruitment models with efficient, automated, and science-based talent acquisition solutions for businesses of all sizes.

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