Responsibilities
- Apply computer science principles, including data structures, algorithms, and architecture.
- Utilize advanced mathematical skills for computations and algorithm development.
- Team up with data engineers to create data and model pipelines.
- Oversee infrastructure and data pipelines for production-ready code.
- Demonstrate comprehensive understanding of applications, including machine learning algorithms.
- Develop algorithms using statistical modeling and maintain scalable machine learning solutions.
- Employ data modeling and evaluation to identify patterns and predict outcomes.
- Implement machine learning algorithms and libraries.
- Lead software engineering and design efforts.
- Explain complex processes to non-technical stakeholders.
- Collaborate with stakeholders to analyze business problems and define resolution scope.
- Analyze large datasets to extract insights and choose appropriate techniques.
- Research and implement best practices to enhance machine learning infrastructure.
- Support engineers and product managers in integrating machine learning into products.
Requirements
- Bachelor's or Master's degree in computer science, machine learning, data science, or related fields with knowledge in knowledge representation.
- 8+ years of experience with at least 3 projects or 5 years of hands-on experience in data science or data engineering.
- Proven experience in developing and delivering NLP solutions using pre-trained models and LLMs for tasks like text classification and named entity recognition.
- Hands-on experience fine-tuning pre-trained models on domain-specific datasets using supervised learning and parameter-efficient techniques.
- Ability to build and manage end-to-end machine learning pipelines, including data ingestion and model training.
- Experience in productionizing and operating NLP services in both batch and real-time environments, including model packaging and API deployment.
Nice to Have
- Experience with knowledge graph stores and semantic technology.
- Strong problem-solving skills, business acumen, and excellent communication skills with both technical and non-technical audiences.
Benefits
- Ongoing learning opportunities, skill development, comprehensive benefits, and a supportive team environment.
Work Arrangement
Hybrid
Team
Co-located agile teams with end-to-end ownership of product, design, development, release, user assistance, and cloud operations capabilities.
Other
- Successful candidates might undergo a background verification with an external vendor.
- Expected Travel: 0 - 10%
- Career Status: Professional
- Employment Type: Regular Full Time
