Machine Learning Engineer

About Eucloid:

Eucloid Data Solutions is a fast-growing AI-consulting firm that enables business growth for its clients through advanced Data Analytics, Machine Learning and Data engineering. Eucloid offers bespoke, full- stack and data- driven approach to solving highly complex and large-scale business problems for some of the biggest Fortune-500 organizations. Eucloid has presence across multiple continents & countries, most notably in US, India, Sweden & Indonesia.

Eucloid has deep partnerships with leading Data & Cloud vendors in the industry. These range from Marketing Cloud solutions (Adobe, Twilio, Google), Customer Data Platforms (Segment, TreasureData, Adobe), Cloud Vendors (Amazon, Microsoft, Google), Machine Learning (H2O.ai, Tensorflow) and Data Products (Snowflake, Databricks, Confluent). Eucloid is also an early adopter and a strong believer in Opensource platforms like DBT, Airflow & Superset.

We take immense pride in our team. We are comprised of high-performing, ambitious, diverse and highly accomplished individuals with educational backgrounds from Top-tier institutes such as IITs/NITs/BITS/DTU/IIMs, World-class Consulting, Analytics, Product & Tech orgs such as Walmart/American Express Accenture/Sapient/EXL/Noon/Citibank/Samsung.

About Co-founders:

Raghvendra Kushwah

Anuj Gupta

About The Role:

Machine Learning / Data Scientist

Key Responsibilities

• Collaborate with cross-functional teams (product, engineering, business stakeholders) to identify business problems and define data science solutions.
• Perform extensive data exploration, cleaning, and feature engineering to prepare data for model development.
• Design, develop, and implement machine learning models (e.g., supervised, unsupervised, deep learning) to address specific business challenges.

  This includes developing and deploying computer vision models for tasks such as object detection, image classification, segmentation, or facial recognition.

• Evaluate model performance using appropriate metrics and conduct rigorous A/B testing or other validation strategies.
• Deploy machine learning models into production environments, ensuring scalability, reliability, and maintainability.
• Monitor deployed models for performance degradation, data drift, and concept drift, and retrain/update as necessary.
• Communicate complex analytical findings and model results clearly and concisely to technical and non-technical audiences.
• Stay up-to-date with the latest advancements in machine learning, artificial intelligence, and data science.
• Contribute to the team's best practices, code reviews, and knowledge sharing.

Required Qualifications

• Education:

  Bachelor's or masters degree in computer science, Data Science, Statistics, Applied Mathematics, Engineering, or a related quantitative field.

• Experience:

  3-5 years of hands-on professional experience in a Machine Learning Engineer or Data Scientist role.

• Programming:

  Strong proficiency in Python, including libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, or Keras.

• Machine Learning:

  Solid understanding of machine learning fundamentals, including algorithms (e.g., regression, classification, clustering, tree-based models), model evaluation, and validation techniques.

• Statistical Analysis:

  Strong statistical foundations and experience with statistical modeling.

• Data Manipulation:

  Experience with SQL for data extraction and manipulation from various databases.

• Problem-Solving:

  Proven ability to translate business problems into data science questions and develop effective solutions.

• Communication:

  Excellent verbal and written communication skills, with the ability to explain complex technical concepts to diverse audiences.

• Computer Vision Fundamentals:

  Foundational understanding of image processing techniques and core computer vision concepts.

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