Senior ML/DL Engineer
About The Position
Senior Data scientist / Machine / Deep Learning Engineer!
We are seeking a talented senior machine learning engineer / data scientist to help us advance our machine learning capabilities. The ideal candidate should be a self-driven, motivated, and independent thinker who is passionate about using data and machine learning to drive business outcomes.
• Develop and implement cutting-edge machine learning models and algorithms for demand forecasting applications.
• Conduct research and experimentation to identify and evaluate new approaches for improving model accuracy and performance.
• Collaborate with cross-functional teams, including business stakeholders, data engineers, and software developers, to deploy and maintain machine learning systems in production.
• Mentor and train junior team members, promoting best practices and fostering a culture of continuous learning and improvement.
• Communicate technical findings and insights to non-technical stakeholders, including executives and other decision-makers.
- 6+ years of hands-on experience in data science and machine learning.
- Expertise in time-series forecasting, with experience working in demand forecasting or related contexts.
- Strong coding skills in Python and SQL, with experience using related open-source libraries and frameworks, including TensorFlow/PyTorch and Pandas.
- Experience building tabular machine learning models using gradient boosting methods and deep learning
- Strong understanding of machine learning systems in production, including good coding practices for testing, reproducibility, and version control.
- Excellent written and verbal communication skills.
Nice to have:
- Degree in Computer Science, Statistics, or related quantitative field.
- Published papers, patents, or professional posts.
- Experience in leveraging deep learning and machine learning in domains such as finance/trading, reinforcement learning, or natural language processing.
- Experience with MLOps and cloud platforms like GCP.
- Experience with workflow orchestration tools like Apache Airflow or Dagster to schedule and monitor machine learning workflows.
- Strong data visualization and data analysis skills.
- Knowledge of code optimization, cloud computing, containerization, and continuous integration/continuous deployment (CI/CD) pipelines.
- Competitive programming and data science (Kaggle like) exp