Verified Job
IT / Software / Data Analyst
Machine Learning Engineer - Python
IT / Software / Data Analyst
#615137
Remote / WFH
Job Description
We are seeking a skilled and innovative Machine Learning Engineer with over 5 years of experience to design, develop, and deploy scalable ML solutions.
You will work closely with data scientists, software engineers, and product teams to solve real-world problems using state-of-the-art machine learning and deep learning techniques.
Key Responsibilities
• Design, build, and optimize machine learning models and pipelines for classification, regression, clustering, recommendation, and forecasting
• Implement and fine-tune deep learning models using frameworks like TensorFlow, PyTorch, or Keras
• Collaborate with cross-functional teams to understand business problems and convert them into technical solutions
• Develop data preprocessing, feature engineering, and model evaluation strategies
• Build and deploy models into production using CI/CD practices and MLOps tools
• Monitor model performance and retrain as necessary to ensure accuracy and reliability
• Create and maintain technical documentation, and provide knowledge sharing within the team
• Stay updated on the latest research, tools, and techniques in machine learning and AI
Required Skills & Experience
• 5+ years of experience in Machine Learning Engineering or Applied Data Science
• Proficiency in Python and ML libraries such as scikit-learn, pandas, NumPy, TensorFlow, or PyTorch
• Solid understanding of mathematics, statistics, and ML/DL algorithms
• Experience with end-to-end ML lifecycle from data collection and cleaning to model deployment and monitoring
• Strong knowledge of SQL and working with large datasets
• Experience deploying ML models on cloud platforms (e.g., AWS, Azure, GCP)
• Familiarity with Docker, Kubernetes, MLflow, or other MLOps tools
• Good understanding of REST APIs, microservices, and backend integration
Nice To Have
• Exposure to NLP, Computer Vision, or Generative AI techniques
• Experience with big data technologies like Spark, Hadoop, or Hive
• Working knowledge of data labeling, AutoML, or active learning
• Experience with feature stores, model registries, or streaming data (Kafka, Flink)
Educational Qualification
• Bachelors or Masters degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field
• Additional certifications in AI/ML are a plus
You will work closely with data scientists, software engineers, and product teams to solve real-world problems using state-of-the-art machine learning and deep learning techniques.
Key Responsibilities
• Design, build, and optimize machine learning models and pipelines for classification, regression, clustering, recommendation, and forecasting
• Implement and fine-tune deep learning models using frameworks like TensorFlow, PyTorch, or Keras
• Collaborate with cross-functional teams to understand business problems and convert them into technical solutions
• Develop data preprocessing, feature engineering, and model evaluation strategies
• Build and deploy models into production using CI/CD practices and MLOps tools
• Monitor model performance and retrain as necessary to ensure accuracy and reliability
• Create and maintain technical documentation, and provide knowledge sharing within the team
• Stay updated on the latest research, tools, and techniques in machine learning and AI
Required Skills & Experience
• 5+ years of experience in Machine Learning Engineering or Applied Data Science
• Proficiency in Python and ML libraries such as scikit-learn, pandas, NumPy, TensorFlow, or PyTorch
• Solid understanding of mathematics, statistics, and ML/DL algorithms
• Experience with end-to-end ML lifecycle from data collection and cleaning to model deployment and monitoring
• Strong knowledge of SQL and working with large datasets
• Experience deploying ML models on cloud platforms (e.g., AWS, Azure, GCP)
• Familiarity with Docker, Kubernetes, MLflow, or other MLOps tools
• Good understanding of REST APIs, microservices, and backend integration
Nice To Have
• Exposure to NLP, Computer Vision, or Generative AI techniques
• Experience with big data technologies like Spark, Hadoop, or Hive
• Working knowledge of data labeling, AutoML, or active learning
• Experience with feature stores, model registries, or streaming data (Kafka, Flink)
Educational Qualification
• Bachelors or Masters degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field
• Additional certifications in AI/ML are a plus
