ML Engineering Lead

2 months ago

bangalore, India ofi Full time

At ofi , we are at the forefront of harnessing cutting-edge technology to revolutionize our operations. We aim to leverage machine learning and artificial intelligence to drive transformative business outcomes and create value for our clients. We are committed to a culture of innovation, diversity, and continuous improvement, where every team member can contribute and thrive.

As a Machine Learning/Artificial Intelligence Engineer Lead, you will be crucial in developing advanced algorithms and models to tackle complex problems. Your expertise will drive the deployment of intelligent systems that enhance our products and services. You will work within a collaborative environment, leveraging data and machine learning to influence business strategies and improve operational efficiency.


Key Responsibilities:

  • Design, develop, and implement state-of-the-art machine learning algorithms and AI models tailored to specific business applications (e.g., classification, regression, clustering, reinforcement learning).
  • Build robust and scalable data pipelines to preprocess, transform, and aggregate data for model training and evaluation.
  • Thoroughly test, validate, and tune models to optimize performance metrics (e.g., accuracy, precision, recall, and F1-score) and ensure robustness against overfitting.
  • Collaborate with data scientists, software developers, and UI/UX designers to integrate machine learning solutions into existing applications and workflows.
  • Establish feedback mechanisms to iterate on models based on user input and real-world performance data.
  • Develop prototypes and proof-of-concept solutions to demonstrate the feasibility and impact of new ideas and technologies.
  • Experiment with cutting-edge tools, libraries, and frameworks (e.g., Keras, XGBoost, BERT) to enhance model performance and capabilities.
  • Implement monitoring systems to track model performance and identify degradation over time, ensuring proactive maintenance and updates.
  • Maintain comprehensive documentation for all models, algorithms, and processes, ensuring transparency and knowledge transfer within the team.
  • Utilize version control systems (e.g., Git, Azure Repos) to manage codebase changes and collaborate effectively with team members.
  • Establish a clear vision and strategy for the machine learning team, aligning it with the organisation's overall goals and foster a culture of collaboration, innovation, and accountability within the team.
  • Lead, mentor, and inspire a team of machine learning engineers, providing guidance on technical and professional development.
  • Ensure best practices in software development, including code quality, version control, testing, and documentation. Conduct thorough code reviews and facilitate knowledge-sharing sessions to enhance the team's skill set.
  • Develop and maintain the infrastructure (DevOps) for deploying, scaling, and monitoring machine learning models.
  • Ensure deployed models comply with data privacy and security regulations. Implement measures to safeguard sensitive data and manage access controls effectively.
  • Keep abreast of the latest research and trends in machine learning and artificial intelligence to inform our strategy and product development.


Qualifications:

  • Bachelor’s or master’s degree in computer science, ML engineering, AI, Data Science, or a related field.
  • Proven 8+ years of experience in developing, deploying and managing machine learning models in production environments.
  • Strong knowledge of data manipulation and analysis libraries (e.g., Pandas, NumPy) and database systems (e.g., SQL, NoSQL).
  • Strong understanding of machine learning concepts and algorithms. Expertise in supervised and unsupervised learning techniques, natural language processing (NLP), computer vision, and time-series analysis.
  • Familiarity with containerisation tools (e.g., Docker, Kubernetes), CI/CD pipelines, and MLOps practices to streamline deployment and monitoring.
  • Experience with big data technologies (e.g., Hadoop, Spark).
  • Knowledge of data engineering and ETL processes.
  • Familiarity with infrastructure as code tools (e.g., Terraform, Ansible).


Preferred Skills:

  • Strong analytical and critical thinking skills, with a focus on problem-solving and data-driven decision-making.
  • Proficiency in programming languages such as Python, R, C++ etc..
  • Experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
  • Solid problem-solving skills and ability to address complex technical challenges.
  • Strong communication skills and ability to work collaboratively in a team environment.

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