Shape the future of intelligent digital experiences by designing and deploying machine learning and generative AI models that power search, recommendation engines, and user behavior analysis. You'll leverage vast datasets—including product catalogs, user queries, and behavioral patterns—to uncover meaningful insights and build scalable solutions that enhance how users interact with digital platforms.
What You’ll Do
- Develop, refine, and deploy ML and deep learning models that directly impact search relevance and personalized recommendations.
- Process and analyze large volumes of structured and unstructured data, including text, images, and user interactions, to extract actionable features.
- Explore emerging techniques in AI, particularly in natural language processing, representation learning, and generative models, and rapidly prototype promising approaches.
- Collaborate with data engineers and senior scientists to scale models into production environments handling terabytes of data on cloud platforms.
- Stay current with advancements in AI research by reviewing academic papers and participating in relevant technical communities.
What We’re Looking For
- Advanced degree in Computer Science, Mathematics, or a related field with strong programming proficiency in Python and solid mathematical grounding.
- At least three years of hands-on experience building scalable machine learning systems in production, preferably in fast-paced environments.
- Deep familiarity with core ML concepts including classification, clustering, information retrieval, ranking, and knowledge graphs.
- Proven ability to conduct exploratory data analysis at scale using SQL on platforms like Redshift or BigQuery.
- Experience with deep learning frameworks such as PyTorch, Keras, or TensorFlow, and techniques like Transformers, RNNs, and transfer learning.
- Background working with big data ecosystems in cloud environments (AWS, GCP, or Azure).
- Strong communication skills in English, both written and verbal, with a collaborative mindset.
Nice to Have
- Hands-on experience with generative AI technologies and large language models (LLMs).
- Active engagement with the latest developments in GenAI research and applications.
Our Environment
We operate on trust and outcomes. There are no rigid schedules or bureaucratic hurdles—just the freedom to work effectively. Our culture emphasizes personal growth, well-being, and shared values. With a virtual-first model and hubs across multiple continents, you can work from anywhere in the region. We support continuous learning through coaching, development programs, and an annual education budget. Regular global events and quarterly ‘DisConnect’ days foster connection and balance. We celebrate work anniversaries, support volunteering, and invest in leadership development. Compensation includes performance bonuses, equity (RSUs or options), referral rewards, and benefits like extended parental leave and mental wellness support.
