We are looking for a skilled AI/ML Engineer to design, develop, and deploy machine learning models and AI solutions. The ideal candidate has strong experience in building scalable ML pipelines, working with large datasets, and deploying models into production environments.
Key Responsibilities:
* Machine Learning & AI Development:
* Build, train, and optimize machine learning models for classification, regression, NLP, CV, or recommendation systems.
* Develop end-to-end ML pipelines, including data preprocessing, feature engineering, model training, and evaluation.
* Research, implement, and optimize deep learning architectures, including CNNs, RNNs, LSTMs, and Transformers.
* Data Engineering:
* Collect, clean, and preprocess large-scale structured and unstructured datasets.
* Build scalable data pipelines using tools like Airflow, Spark, or similar.
* Deployment & MLOps:
* Deploy ML models into production using Docker, Kubernetes, and cloud platforms such as AWS, GCP, or Azure.
* Implement model monitoring, retraining strategies, and performance optimization.
* Work with APIs, microservices, and CI/CD pipelines for model integration.
* Collaboration:
* Work closely with product, engineering, and data teams to identify AI use cases.
* Explain complex models and outputs to non-technical stakeholders.
Required Skills:
* Technical Skills:
* Strong proficiency in Python, including NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch.
* Knowledge of NLP, Computer Vision, or Generative AI techniques.
* Experience with model deployment and MLOps using Docker, Kubernetes, or MLflow.
* Understanding of data structures, algorithms, and machine learning fundamentals.
* Tools & Technologies:
* ML frameworks: TensorFlow, PyTorch.
* Cloud platforms: AWS, GCP, Azure.
* Databases: SQL, NoSQL.
* Version control: Git.
* Pipeline tools: Airflow, Prefect, Kubeflow.
Preferred Qualifications:
* Master’s or Bachelor’s degree in Computer Science, AI, Data Science, or related fields.
* Experience with LLMs, vector databases (Pinecone, FAISS), or prompt engineering.
* Experience in deploying production-grade AI systems.
* Knowledge of reinforcement learning or generative AI.
Benefits:
* Competitive salary.
* Growth opportunities in advanced AI projects.
* Chance to work with a skilled and innovative team.
