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Role-Machine Learning Engineer

Skills required- Python, AI, ML

Location- Bangalore, Mumbai

Year of experience - 6 to 10 years

Job description:

• Machine Learning Engineers will work on all AI and ML technologies - machine learning, knowledge graphs, cognitive etc. – to Design, develop and implement solutions.
• Experience with Machine Learning algorithms.
• Expertise in Python
• Deep understanding of data structures and algorithms.

We are looking for a skilled Machine Learning Engineer with expertise in Python and hands-on experience in building, training, and deploying machine learning and deep learning models. The ideal candidate will have prior experience taking models from experimentation to production, along with knowledge of modern ML/DL frameworks and cloud environments.

Key Responsibilities:

• Design, train, and fine-tune machine learning and deep learning models
• Perform model inference, testing, and optimization for production-scale applications
• Deploy ML models using Docker and AWS cloud services
• Work closely with cross-functional teams to translate business needs into ML solutions
• Manage databases (SQL, MongoDB) and build efficient data pipelines
• Monitor deployed models to ensure accuracy, scalability, and reliability

Requirements:

• 2–5 years of experience as an ML Engineer or in a related role
• Strong proficiency in Python and ML/DL libraries (TensorFlow, PyTorch, Scikit-learn)
• Proven experience with model training, inference, and deployment
• Experience with AWS, Docker, and working with SQL/MongoDB databases
• Bachelor’s degree in Computer Science, Engineering, or related field (Master’s degree is a plus)

About IDfy

IDfy is an Integrated Identity Platform offering products and solutions for KYC, KYB, Background Verifications, Risk Assessment, and Digital Onboarding. We establish trust while delivering a frictionless experience for you, your employees, customers and partners.

Only IDfy combines enterprise-grade technology with business understanding and has the widest breadth of offerings in the industry. With more than 12+ years of experience and 2 million verifications per day, we are pioneers in this industry.

Our clients include HDFC Bank, Induslnd Bank, Zomato, Amazon, PhonePe, Paytm, HUL and many others.

We have successfully raised $27M from Elev8 Venture Partners, KB Investments & Tenacity Ventures!

We work fully onsite on all days of the week from our office in Andheri East, Mumbai

We're a perfect match if you have-

• 4-8 years of experience in Machine Learning, NLP, and LLM-based solutions.
• Strong expertise in fine-tuning and deploying LLMs (GPT-4, Llama, Mistral, or custom models).
• Experience with RAG-based architectures, including vector embeddings (FAISS, ChromaDB, Weaviate, Pinecone, or similar).
• Hands-on with agentic RAG, sliding window chunking, and efficient context retrieval techniques.
• Deep understanding of privacy AI use cases, including contract analysis, regulatory classification, and PII mapping.
• Proficiency in Python and frameworks like PyTorch, TensorFlow, JAX, Hugging Face, or LangChain.
• Experience in building scalable AI APIs and microservices.
• Exposure to MLOps practices, including model monitoring, inference optimization, and API scalability.
• Experience working with at least one cloud provider (AWS, GCP, or Azure).

Good-to-Have Skills

• Experience in hybrid AI architectures combining vector search + relational databases.
• Familiarity with functional programming languages (Go, Elixir, Rust, etc.).
• Understanding of privacy compliance frameworks (DPDP Act, GDPR, CCPA, ISO 27701).
• Exposure to Kubernetes, Docker, and ML deployment best practices.
• Contributions to open-source LLM projects or privacy AI research.

In this role you will:

• Develop and fine-tune LLMs for contract analysis, regulatory classification, and risk assessment.
• Implement Retrieval-Augmented Generation (RAG) using vector embeddings and hybrid DB-based querying to power DPIA and compliance workflows.
• Build AI-driven contract analysis systems to detect dark patterns, classify clauses, and provide remediation suggestions.
• Develop knowledge graph-based purpose taxonomies for privacy policies and PII classification.
• Automate data discovery for structured and unstructured data, classifying it into PII categories.
• Optimize sliding window chunking, token-efficient parsing, and context-aware summarization for legal and compliance texts.
• Build APIs and ML services for deploying models in a high-availability production environment.
• Collaborate with privacy, legal, and compliance teams to build AI solutions that power Privy’s data governance tools.
• Stay ahead of the curve with agentic RAG, multi-modal LLMs, and self-improving models in the compliance domain.

• Design, build, train, and deploy state-of-the-art NLP models for various applications.
• Develop and implement algorithms for text classification, named entity recognition, topic modeling, and sentiment analysis.
• Work with large text datasets, including data cleaning, preprocessing, and feature engineering.
• Integrate NLP models into existing software systems and develop new APIs.
• Collaborate with product managers and software engineers to understand user needs and translate them into ML solutions.
• Evaluate and benchmark model performance, identifying areas for improvement.
• Stay up-to-date with the latest research and advancements in NLP and machine learning.
• Optimize models for performance, scalability, and efficiency.
• Contribute to the ML platform and infrastructure development.
• Write clean, maintainable, and well-documented code.
• Participate in code reviews and knowledge sharing sessions.
• Ensure the ethical and responsible use of AI technologies.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Data Science, or a related field.
• 3+ years of experience in machine learning and NLP development.
• Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers).
• Strong understanding of NLP concepts, including embeddings (Word2Vec, GloVe), sequence models (RNNs, LSTMs, GRUs), and attention mechanisms.
• Experience with modern NLP architectures like Transformers (BERT, GPT, etc.).
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps tools is a plus.
• Solid software engineering skills, including version control (Git) and CI/CD pipelines.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration abilities.
• Experience with large-scale data processing frameworks (e.g., Spark) is beneficial.
• Familiarity with other ML domains is a plus.

• Lead the design, development, and implementation of machine learning models and algorithms for various applications.
• Build and maintain robust, scalable, and efficient machine learning pipelines for data preprocessing, model training, and deployment.
• Collaborate with data scientists, software engineers, and product managers to translate business requirements into technical solutions.
• Evaluate and select appropriate machine learning techniques and tools for specific problems.
• Optimize model performance, accuracy, and efficiency through rigorous experimentation and validation.
• Develop and implement strategies for deploying ML models into production environments.
• Stay up-to-date with the latest research and advancements in machine learning, deep learning, and AI.
• Mentor junior machine learning engineers and data scientists.
• Contribute to the architectural design of AI/ML systems and platforms.
• Ensure best practices in MLOps, including monitoring, versioning, and CI/CD for ML models.
• Troubleshoot and resolve complex issues related to ML model performance and deployment.

• Master's or Ph.D. in Computer Science, Data Science, Artificial Intelligence, or a related quantitative field.
• Minimum of 7 years of experience in machine learning engineering, with at least 3 years in a lead or senior role.
• Proven experience in designing, building, and deploying machine learning models in production.
• Strong expertise in machine learning algorithms (e.g., supervised, unsupervised, reinforcement learning) and deep learning frameworks (e.g., TensorFlow, PyTorch).
• Proficiency in programming languages such as Python, R, or Scala.
• Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, SciPy).
• Familiarity with cloud platforms (AWS, Azure, GCP) and their ML services.
• Knowledge of big data technologies (e.g., Spark, Hadoop) is a plus.
• Excellent understanding of software development best practices, including version control and testing.
• Strong problem-solving skills and the ability to work independently in a remote setting.
• Exceptional communication and collaboration skills.
• Experience with MLOps practices and tools is highly desirable.

• Design, build, and deploy sophisticated machine learning models and algorithms.
• Conduct research and development to explore new ML techniques and technologies.
• Collaborate with data scientists, software engineers, and product managers to integrate ML solutions into products and services.
• Develop and maintain scalable ML pipelines for data preprocessing, model training, evaluation, and deployment.
• Monitor and optimize the performance of deployed ML models, identifying areas for improvement.
• Perform data analysis and feature engineering to enhance model accuracy and effectiveness.
• Stay abreast of the latest research and industry trends in AI and machine learning.
• Mentor junior ML engineers and contribute to the team's technical growth.
• Communicate complex technical concepts and findings to both technical and non-technical stakeholders.
• Ensure the ethical and responsible application of AI technologies.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Statistics, or a related quantitative field.
• Minimum of 5 years of hands-on experience in machine learning engineering or data science.
• Proficiency in programming languages such as Python, and experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
• Strong understanding of statistical modeling, deep learning, and various ML algorithms.
• Experience with MLOps practices and tools for model deployment and management.
• Excellent problem-solving, analytical, and critical thinking skills.
• Proven ability to lead projects and mentor team members.
• Strong communication and presentation skills.
• Familiarity with containerization technologies like Docker and Kubernetes is a plus.

• Design, develop, and implement machine learning models and algorithms.
• Build and maintain scalable data pipelines for ML model training and inference.
• Deploy ML models into production environments using MLOps best practices.
• Evaluate and optimize model performance, accuracy, and efficiency.
• Collaborate with data scientists and domain experts to define ML project requirements.
• Stay current with the latest advancements in machine learning research and technologies.
• Develop and implement robust testing and validation strategies for ML models.
• Contribute to the architecture and design of ML platforms and infrastructure.
• Mentor junior machine learning engineers and share knowledge.
• Present findings and model performance to technical and non-technical stakeholders.

• Master's or Ph.D. in Computer Science, Machine Learning, Statistics, or a related quantitative field.
• 5+ years of experience in machine learning engineering or data science roles.
• Strong programming skills in Python, with extensive experience using ML libraries (TensorFlow, PyTorch, scikit-learn).
• Solid understanding of ML algorithms, statistical modeling, and data mining techniques.
• Experience with MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, Kubernetes).
• Proficiency in working with large datasets and distributed computing frameworks (e.g., Spark).
• Experience with cloud platforms like AWS, Azure, or GCP.
• Excellent analytical and problem-solving abilities.
• Strong communication and collaboration skills.