Location: India
Experience: 1-2 Years
Salary: 4 to 8 LPA

About the Role
We are looking for a highly skilled Machine Learning Engineer to join our team and contribute to building intelligent, scalable, and production-ready AI solutions across our products. The ideal candidate will have hands-on experience with developing ML models, working with large datasets, and deploying AI-driven features into real-world applications.

Key Responsibilities:

·   Develop, train, and optimize machine learning models for various product use cases (recommendation systems, NLP features, predictive analytics,classification models, etc.)
·   Implement end-to-end ML pipelines—from data preprocessing to model training, evaluation, deployment, and monitoring.
·  Work closely with backend, product, and data teams to integrate ML solutions into production.
·  Improve existing AI features like candidate job matching, smart sourcing, automated job applications, CV parsing, and intelligent chat i    interactions.
·  Conduct A/B testing and model performance evaluation to ensure high accuracy and reliability.
·  Research and experiment with new algorithms, frameworks, and AI advancements to enhance product capabilities.
·  Optimize models for efficiency, scalability, and low-latency real-time performance.
·  Maintain clear documentation and follow best coding, security, and data-handling practices.

Required Skills & Qualifications:
·       Bachelor’s or Master’s degree in Computer Science, Data Science, AI, Machine Learning, or a related field.
·       1+ years of hands-on experience in ML model development and deployment.
·       Strong proficiency in Python and ML/data libraries such as TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy.
·       Experience with NLP libraries (Transformers, spaCy, NLTK) is a strong advantage.
·       Solid understanding of data structures, algorithms, probability, and statistics.
·       Experience building and using APIs for inference (FastAPI, Flask, etc.).
·       Knowledge of cloud services (AWS/GCP/Azure) and containerization (Docker).
·       Experience with vector databases, embeddings, or LLM-based applications is a plus.
·       Familiarity with MLOps tools such as MLflow, SageMaker, Kubeflow, or similar.

     Preferred Qualifications:

·  Experience with recommendation engines or talent-matching systems.
·  Understanding of prompt engineering and LLM fine-tuning.
·  Experience in deploying AI-powered features in production environments.

Soft Skills:

·  Strong analytical and problem-solving skills.
·  Ability to work independently and in a fast-paced environment.
·  Excellent communication and documentation skills.
·  Strong ownership mentality and focus on delivery.