Machine Learning Engineer

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 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 team's 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