DE&A - AIML - Conversational Systems @ Zensar

Machine Learning Engineer - 7 Years Experience

Location: Hyd or NCR

About the Role:

We are seeking a highly skilled and experienced Machine Learning Engineer to join our dynamic team. As a Machine Learning Engineer, you will be responsible for the design, development, deployment, and maintenance of machine learning models and systems that drive our [mention specific business area or product, e.g., recommendation engine, fraud detection system, autonomous vehicles]. You will work closely with data scientists, software engineers, and product managers to translate business needs into scalable and reliable machine learning solutions. This is a key role in shaping the future of CBRE and requires a strong technical foundation combined with a passion for innovation and problem-solving.

Responsibilities:

Model Development Deployment:
Design, develop, and deploy machine learning models using various algorithms (e.g., regression, classification, clustering, deep learning) to solve complex business problems.
Select appropriate datasets and features for model training, ensuring data quality and integrity.
Implement and optimize model training pipelines, including data preprocessing, feature engineering, model selection, and hyperparameter tuning.
Deploy models to production environments using containerization technologies (e.g., Docker, Kubernetes) and cloud platforms (e.g., AWS, GCP, Azure).
Monitor model performance in production, identify and troubleshoot issues, and implement model retraining and updates as needed.
Infrastructure Engineering:
Develop and maintain APIs for model serving and integration with other systems.
Write clean, well-documented, and testable code.
Collaborate with software engineers to integrate models into existing products and services.
Research Innovation:
Stay up-to-date with the latest advancements in machine learning and related technologies.
Research and evaluate new algorithms, tools, and techniques to improve model performance and efficiency.
Contribute to the development of new machine learning solutions and features.
Proactively identify opportunities to leverage machine learning to solve business challenges.
Collaboration Communication:
Collaborate effectively with data scientists, software engineers, product managers, and other stakeholders.
Communicate technical concepts and findings clearly and concisely to both technical and non-technical audiences.
Participate in code reviews and contribute to the teams knowledge sharing.

Qualifications:

Experience: 7+ years of experience in machine learning engineering or a related field.
Technical Skills:
Programming Languages: Proficient in Python and experience with other languages (e.g., Java, Scala, R) is a plus.
Machine Learning Libraries: Strong experience with machine learning libraries and frameworks such as scikit-learn, TensorFlow, PyTorch, Keras, etc.
Data Processing: Experience with data manipulation and processing using libraries like Pandas, NumPy, and Spark.
Model Deployment: Experience with model deployment frameworks and platforms (e.g., TensorFlow Serving, TorchServe, Seldon, AWS SageMaker, Google AI Platform, Azure Machine Learning).
Databases: Experience with relational and NoSQL databases (e.g., SQL, MongoDB, Cassandra).
Version Control: Experience with Git and other version control systems.
DevOps: Familiarity with DevOps practices and tools.
Strong understanding of machine learning concepts and algorithms: Regression, Classification, Clustering, Deep Learning etc.
Soft Skills:
Excellent problem-solving and analytical skills.
Strong communication and collaboration skills.
Ability