Machine Learning Engineer

What We Do

• Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
• Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.
• Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.
• Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.
• Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
• Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.

Our Partnerships

• Amazon Web Services
• Google Cloud
• Astronomer
• Databricks
• Kaszek
• Product Minds
• H2O.ai
• Soda

Our Values

• We are Data Nerds
• We are Open Team Players
• We Take Ownership
• We Have a Positive Mindset
Curious about what we’re up to? Check out our case studies and dive into our blog post to learn more about our culture and the exciting projects we’re working on!

Responsibilities

• Develop and optimize ML models, ensuring scalability, monitoring, and integration with MLOps best practices.
• Implement client requirements, from exploratory data analysis (EDA) to feature engineering and model lifecycle management.
• Build ML Proof of Concepts (POCs) to validate and refine solutions.
• Optimize models for performance, latency, memory, and throughput.
• Apply statistical analysis techniques and develop regression models.
• Design and maintain feature stores and data pipelines for ML workflows.
• Research and implement emerging ML/AI techniques to enhance solutions.
• Collaborate with stakeholders to align technical solutions with business needs.

Required Skills

• Experience implementing ML-based systems, including model lifecycle management, monitoring, and MLOps pipeline setup.
• Strong proficiency in Python (Pandas, Numpy, Jupyter, Scikit-Learn, XGBoost, Plotly).Knowledge of SQL
• Experience with cloud platforms (AWS, GCP, Azure).

Nice to Have Skills

• Experience with ML workflows (Airflow, MLflow, H2OAI, Databricks, or similar).
• Background in modern LLM technologies.
• Understanding of Deep Learning frameworks (Keras, PyTorch, TensorFlow).Basic knowledge of Docker.

Perks

• Remote-first culture – work from anywhere!
• Wellhub or sports club stipend to stay active
• AWS Databricks certifications fully covered (reward salary increase for AWS certifications!)
• Food credits via Pedidos Ya – because great work deserves great food.
• Birthday off + an extra vacation week (Mutt Week! ️)
• Referral bonuses – help us grow the team get rewarded!
• ✈️ ️ Annual Mutters' Trip – an unforgettable getaway with the team!

Originally posted on Himalayas