Overview-

Reporting to the Director of Machine Learning Engineering the role requires a skilled Machine Learning Engineer to design, build, and deploy machine learning models that will help us derive actionable insights and solve complex problems. The ideal candidate will have a strong background in data science, programming, and machine learning algorithms and will be passionate about leveraging data to drive business decisions.

Responsibilities

• Build and deploy production grade Machine Learning models.
• Work in the full lifecycle of ML model development, from data preparation and feature engineering to model training, evaluation, and deployment.
• Deep technical proficiency in applying a variety of machine learning algorithms, techniques, and frameworks to solve complex business challenges.
• Assemble modules into end-to-end systems, ensuring seamless integration and functionality.
• Collaborate closely with Data Scientists to facilitate highly productive experimentation, model construction, and validation, fostering a sense of teamwork and shared success.
• Exceptional programming skills in Python, with popular deep learning and natural language processing (NLP) tools and libraries, including Scikit-learn, Pandas, PyTorch, TensorFlow, or other leading deep learning frameworks, NLTK and spaCy for natural language processing tasks
• Leverage Jupyter Notebooks for prototyping, experimentation, and collaboration.
• Contribute to the continuous improvement of our machine learning systems by staying abreast of advancements in software engineering and machine learning.

Technical Skills

• Strong expertise in programming languages - Python, R, or Scala and technologies like Tensorflow, PyTorch, Kubernetes, Spark, Airflow, Kafka and Opensource LLMs.
• Experience in working with petabyte scale data sets and developing ML frameworks in Databricks, Snowflake or similar large platforms.
• Proficiency in machine learning and familiarity with open-source machine learning ecosystems.
• Proficiency with CI/CD solutions in the context of MLOps and LLMOps including automation with IaC (ex: terraform).

Soft Skills

• Excellent communication and collaboration skills.
• Strategic thinker with a strong analytical mindset and problem-solving abilities.