GenAI Developer Job Openings At Sapiens – Apply Now!

Qualifications

• Education: Bachelor’s or Master’s in Computer Science, Data Science, AI/ML, or a related field.
• Experience: 2+ years in AI/ML, with at least 1 years in Generative AI model development and deployment.
• Certifications (optional): AI/ML certifications or training in GenAI frameworks is a plus.

• Technical Proficiency
  • Strong expertise in GenAI frameworks and tools (e.g., Hugging Face, OpenAI API, DeepSpeed, DALL-E, and others).
  • Proficient in programming languages such as Python and experience with ML libraries such as TensorFlow, PyTorch, Keras, etc.
  • Solid understanding of transformer architectures, attention mechanisms, LLM fine-tuning, and reinforcement learning techniques.
  • Familiarity with machine learning techniques and algorithms
• Data Engineering & MLOps
  • Hands-on experience with data pipelines and working knowledge of MLOps tools like Docker, Kubernetes, MLflow, and cloud platforms (AWS/Azure/GCP).
  • Proficient in managing large-scale datasets, implementing ETL processes, and ensuring data quality for training models.
• Problem-Solving & Analytical Skills
  • Demonstrated ability to break down complex business requirements and design scalable GenAI solutions that address these needs.
  • Strong skills in debugging, model interpretability, and addressing model bias.
• Communication & Collaboration
  • Good verbal and written communication skills to explain technical concepts to stakeholders.
  • Experience collaborating across multidisciplinary teams, including data engineers, MLOps, and business stakeholders.

Preferred Skills:

• Experience with large language models, text generation, and language understanding tasks
• Experience with image generation and computer vision techniques
• Knowledge of reinforcement learning and its application to generative AI.
• Experience with model explainability, ethical AI, and interpretability techniques.
• Experience in deploying GenAI models for industry-specific applications (e.g., Insurance , healthcare, finance, customer service).
• Knowledge of frontend/backend frameworks and API development.

Job Description and Responsibilities:

• Model Development & Optimization
  • Design, develop, and fine-tune Generative AI models, including transformer-based architectures, GANs, VAEs, image generation models and other advanced models.
  • Implement techniques for model optimization, such as quantization, pruning, and distillation, to ensure efficient model performance.
  • Experiment with different architectures, hyperparameters, and training methodologies to optimize model performance
  • methodologies to optimize model performance
• Data Pipeline & Infrastructure
  • Develop robust data pipelines to support generative model training and fine-tuning processes, ensuring data quality and availability.
  • Work closely with MLOps and data engineering teams to streamline model deployment, monitoring, and version control.
• Application Development & Integration
  • Build end-to-end Generative AI applications, from prototyping to deployment, ensuring seamless integration with existing systems.
  • Design APIs and other interfaces for integrating GenAI models into various applications.
• Performance Monitoring & Model Improvement
  • Set up monitoring tools and frameworks to track model performance and accuracy over time, implementing model retraining where necessary.
  • Address issues related to model drift, retraining, and update requirements for enhanced model effectiveness.
• Research & Innovation
  • Stay updated with the latest developments in GenAI, ML, and NLP, driving continuous innovation within the team.
  • Present research findings within internal teams to contribute to our thought leadership