Machine Learning Engineer

2 days ago

india Luxoft Full time

Project Description:

Machine Learning Engineer to join our team and help design, implement, and maintain cutting-edge machine learning models that drive insights, automation, and product improvements. You will collaborate with software engineers, and product teams to develop scalable ML solutions for real-world problems. Your expertise will contribute to building end-to-end machine learning pipelines and improving model performance across various projects.


Responsibilities:

Model Development and Deployment:

  • Design, implement, and optimize machine learning models using techniques like regression, classification, clustering, and deep learning.
  • Build end-to-end machine learning pipelines, from data collection to model deployment.

Data Processing and Feature Engineering:

  • Collaborate with data engineers to acquire, preprocess, and clean large-scale datasets.
  • Design and implement feature extraction, transformation, and selection methods to improve model performance.

Model Evaluation and Optimization:

  • Use metrics like accuracy, precision, recall, F1-score, ROC-AUC, and others to evaluate model performance.
  • Perform hyperparameter tuning, cross-validation, and model debugging to enhance accuracy and efficiency.

Collaboration with Cross-functional Teams:

  • Partner with data scientists, software engineers, and product managers to deliver data-driven solutions.
  • Translate business requirements into technical specifications for machine learning projects.

Automation and Scalability:

  • Develop scripts and tools to automate data processing, model training, and evaluation pipelines.
  • Work on scaling models and optimizing runtime performance for large datasets and real-time applications.

Stay Updated:

  • Keep up to date with the latest advancements in machine learning, AI, and relevant technologies.
  • Experiment with emerging techniques like transfer learning, reinforcement learning, and generative models.


Mandatory Skills Description:

  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Mathematics, or related field.
  • 4-5 years of hands-on experience in machine learning, data science, or a related role.
  • Experience in designing, training, and deploying machine learning models in production environments.
  • Strong proficiency in Python, including libraries such as TensorFlow, PyTorch, Scikit-learn, Keras, etc.
  • Expertise in machine learning algorithms, statistical modeling, and deep learning.
  • Experience with data processing libraries (Pandas, NumPy) and visualization tools (Matplotlib, Seaborn).
  • Solid understanding of databases and data warehousing.
  • Strong problem-solving skills and ability to work in a collaborative environment.
  • Excellent communication skills, with the ability to explain complex concepts to non-technical stakeholders.
  • Experience with MLOps tools for model monitoring, versioning, and pipeline automation (e.g., MLflow, Kubeflow, Airflow) is a plus.


Nice-to-Have Skills Description:

  • Experience working with big data tools (e.g., Spark, Hadoop) or real-time streaming data (Kafka, Flink).
  • Understanding of natural language processing (NLP), computer vision (CV), or reinforcement learning (RL).
  • Knowledge of software development best practices, including version control (Git), CI/CD pipelines, and containerization (Docker, Kubernetes).

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