Shape the future of AI-driven customer experiences by leading the development of intelligent, data-powered features. In this role, you'll design, build, and deploy machine learning and generative AI solutions that directly address customer needs and deliver clear, measurable business value. You'll work at the intersection of data science, product, and engineering to advance core AI initiatives and improve how users interact with our platform.
What You’ll Do
- Lead end-to-end development of AI and ML features—from concept to production—with a focus on customer impact and product enhancement.
- Build and refine evaluation frameworks to measure performance, ensure quality, and demonstrate return on investment for AI integrations.
- Partner with product, design, and engineering teams to rapidly deliver reliable, scalable AI solutions aligned with strategic goals.
- Translate technical capabilities and limitations into clear insights for cross-functional stakeholders, guiding product decisions with data.
- Develop and deploy models using transformer architectures, embeddings, and modern deep learning techniques to power intelligent workflows.
What We’re Looking For
- At least 5 years of hands-on experience in applied machine learning and data science, with a proven ability to deliver customer-facing AI solutions that drive measurable results.
- Strong proficiency in Python, ML frameworks (e.g., PyTorch, TensorFlow), and data manipulation tools like NumPy, pandas, and SQL.
- Experience working with RESTful APIs and large-scale datasets to inform product development and optimization.
- Deep understanding of statistical modeling, AI/ML methodologies, and NLP applications, with a focus on shipping impactful features.
- Familiarity with deploying models in cloud environments (AWS, Azure, GCP) and integrating with platforms like OpenAI or Anthropic.
Preferred Experience
- Prototyping with emerging AI technologies to assess real-world applicability.
- Designing and analyzing A/B tests to validate feature effectiveness.
- Working with OpenSearch or ElasticSearch for model integration.
- Java development, ML-Ops practices, and secure model deployment.
- Contributing to ethical AI frameworks, including bias mitigation and model security.
