As part of our forward-thinking team, you will contribute to building and refining our internal product library, specifically focused on solving complex business problems related to prediction and recommendation. Your expertise will play a pivotal role in shaping products that provide value to our clients, leveraging the power of machine learning and deep learning. 

Responsibilities

Enhancing Product Features with Machine Learning Algorithms

• You will work on integrating the latest machine learning models into our product suite, including advanced algorithms for product recommendations, real-time predictions, fraud detection, and offer personalization.
• Research and experiment with novel methodologies to improve the current systems, ensuring that we stay ahead of technological advancements.

Collaboration and Model Development

• Collaborating closely with client teams to onboard data and create models that generate predictions, ensuring they align with business objectives and provide actionable results.
• You will be instrumental in building automations around machine learning algorithms, creating seamless, one-click solutions for predictions and recommendations.

Data Engineering and Feature Engineering

• Analyze large datasets, performing extensive data wrangling operations to ensure clean, quality data input for models.
• Engineer new features and apply statistical treatments to filter and refine the data, boosting model accuracy and performance.

Testing, Model Tuning, and Scalability

• Conduct rigorous testing to evaluate the performance of existing models, tuning them to improve accuracy and efficiency.
• Scale models to handle larger datasets, running multi-fold evaluations and defining success criteria, ensuring robust performance at scale.

Deep Learning and Advanced Techniques

• You will contribute to building models using deep learning techniques, focusing on delivering high-performance, scalable solutions that meet business requirements.
• Demonstrate and deepen your understanding of machine learning concepts such as regression, classification, matrix factorization, and K-fold validation to continuously improve the product suite.

Staying Current with Emerging Technologies

• Constantly evolve by staying up-to-date with the latest advancements in machine learning and AI.
• Your work will encompass cutting-edge technologies and frameworks, ensuring we always use the best tools and techniques to solve our clients’ business challenges.

Qualifications

Minimum Qualifications

1. Education. A Master's or PhD in a quantitative discipline (e.g., Statistics, Mathematics, Economics, Computer Science) is highly preferred, reflecting your strong analytical and problem-solving capabilities.
2. Deep Learning Expertise. Extensive experience in working with deep learning frameworks such as TensorFlow, PyTorch, or Keras. You should have hands-on experience with a wide range of deep learning projects, particularly those involving multimodal data applications.
3. Generative AI Expertise. Proven track record working with generative AI models, such as RAG, VAEs, and Transformers. Experience in applying these models at scale, especially in areas like content creation or data augmentation, will be crucial.
4. Programming & Big Data Technologies. Expertise in Python programming is essential, as well as proficiency with big data/cloud technologies (e.g., Databricks, Apache Spark). A minimum of 4-5 years of hands-on experience with these tools will be expected.
5. Recommender Systems & Real-Time Predictions. Expertise in developing sophisticated recommender systems and real-time prediction frameworks. You should be comfortable implementing and optimizing algorithms that deliver personalized user experiences.
6. Machine Learning Algorithms. A deep understanding and practical experience with a wide range of machine learning algorithms, including but not limited to logistic regression, random forests, XGBoost, advanced neural networks, and ensemble methods.
7. Model Development and Performance Tuning. You should be comfortable running performance tests on machine learning models and applying advanced techniques to improve model accuracy and efficiency.

Desirable Qualifications

1. Generative AI Tools Proficiency. Experience with generative AI tools and platforms such as OpenAI or Hugging Face Transformers would be highly beneficial, particularly for improving content creation and data augmentation.
2. Databricks & Unity Catalog. Familiarity with Databricks and Unity Catalog for data management, model deployment, and tracking will give you a strong edge in this role. Experience in these tools ensures that you can manage large-scale data pipelines and maintain model performance.
3. CI/CD Tools Knowledge. A working knowledge of continuous integration and delivery (CI/CD) tools such as Git and Bitbucket is desirable. This will help streamline model deployment and integrate changes seamlessly into production environments.

Why Join Us?

By joining our team, you will be part of a fast-moving, innovative group dedicated to creating transformative solutions. Your contributions will directly impact our clients' ability to navigate complex business challenges using predictive analytics and AI-driven insights. Whether you are enhancing existing models or building new features from the ground up, you will be working at the cutting edge of machine learning and AI technologies. This is an exceptional opportunity to grow your career while shaping the future of data-driven decision-making.

If you are a forward-thinking individual with a passion for solving complex problems using machine learning and AI, we would love to have you on our team.