job summary:
we are looking for highly motivated and analytical machine learning engineers with 1-3 years of experience in building scalable, production-ready ai/ml models. this role involves working on complex business problems using advanced ml/dl techniques across domains such as natural language processing (nlp), computer vision, time series forecasting, and generative ai.
you will be responsible for end-to-end model development, deployment, and performance tracking while collaborating with cross-functional teams including data engineering, devops, and product.
location: noida / gurugram / indore / bengaluru / pune / hyderabad
experience: 1-3 years
education: be / b.tech / m.tech / mca /
key responsibilities:
model development & experimentation
- design and build machine learning models for nlp, computer vision, and time series prediction using supervised, unsupervised, and deep learning techniques.
- conduct experiments to improve model performance via architectural modifications, hyperparameter tuning, and feature selection.
- apply statistical analysis to validate and interpret model results.
- evaluate models using appropriate metrics (e.g., accuracy, precision, recall, f1-score, auc-roc).
data handling & feature engineering
- process large structured and unstructured datasets using python, pandas, and dataframe apis.
- perform feature extraction, transformation, and selection tailored to specific ml problems.
- implement data augmentation and enrichment techniques to enhance training quality.
model deployment & productionization
- deploy trained models to production environments using cloud platforms such as aws (especially sagemaker).
- containerize models using docker and orchestrate deployments with kubernetes.
- implement monitoring, logging, and automated retraining pipelines for model health tracking.
collaboration & innovation
- collaborate with data engineers and architects to ensure smooth data flow and infrastructure alignment.
- explore and adopt cutting-edge ai/ml methodologies and genai frameworks (e.g., langchain, gpt-3).
- contribute to documentation, versioning, and knowledge-sharing across teams.
- drive innovation and continuous improvement in ai/ml delivery and engineering practices.
mandatory technical skills:
- languages & tools: python (pandas, numpy, scikit-learn, tensorflow/pytorch)
- model development: deep learning, nlp, time series, computer vision
- cloud platforms: aws (especially sagemaker)
- model deployment: docker, kubernetes, rest apis
- ml ops: model monitoring, performance logging, ci/cd
- frameworks: langchain (for genai), transformers, hugging face
preferred / good to have:
- experience with foundation model tuning and prompt engineering
- hands-on with generative ai (gpt-3/4, openai apis, langchain integrations)
- certifications: aws certified machine learning - specialty
- experience with version control (git), and experiment tracking tools (mlflow, weights & biases)
soft skills:
- excellent communication and presentation abilities
- strong analytical and problem-solving mindset
- ability to work in collaborative, fast-paced environments
- curiosity to learn emerging technologies and apply them to real-world problems
