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Job Summary
Synechron is seeking a skilled Python GenAI Developer to advance our artificial intelligence and machine learning capabilities within our digital innovation teams. This role involves designing, developing, and deploying AI solutions leveraging generative models, natural language processing, and cloud-based environments. The ideal candidate will collaborate closely with cross-functional teams to integrate AI-driven features, stay updated on the latest tech trends, and contribute to strategic AI initiatives that enhance business value.
Software Requirements
Required Software Proficiency:
Python (latest stable version) — extensive experience in developing AI and ML applications with a focus on generative AI models
Generative AI frameworks: PyTorch, TensorFlow, or similar — proven experience in training and deploying advanced models, including GPT or equivalent architectures
Cloud platforms: AWS, GCP, or Azure — knowledge of deploying AI models in cloud environments
NLP libraries: Hugging Face Transformers, SpaCy — experience with language models and NLP pipelines
Version Control: Git — experience managing code repositories and collaborative development workflows
Preferred Software Skills:
Data processing tools: Pandas, NumPy — skills in handling large datasets for training models
Deployment tools: Docker, Kubernetes — experience containerizing AI models for production
Model optimization: ONNX, TensorRT — experience in model compression and inference acceleration
Overall Responsibilities
Design, develop, and optimize generative AI models for natural language processing, image generation, or other AI tasks
Collaborate with product teams to identify use cases and translate business requirements into AI solutions
Fine-tune pre-trained models, implement transfer learning, and innovate with new architectures
Conduct model evaluations, performance tuning, and validation to ensure deployment-ready solutions
Maintain detailed technical documentation, including model architecture, training procedures, and deployment guidelines
Stay informed about emerging trends in AI/ML, particularly in Generative AI, and incorporate best practices into ongoing projects
Provide technical expertise and support to team members during model development, deployment, and troubleshooting
Technical Skills (By Category)
Programming Languages:
Essential: Python — primary language for model development and scripting
Preferred: Knowledge of C++ or Java for integration and performance optimization
Databases/Data Management:
Experience with NoSQL and relational databases to store training data, logs, or model metadata
Cloud Technologies:
Deployment and management of models on cloud platforms like AWS SageMaker, Google Vertex AI, or Azure ML services
Frameworks and Libraries:
PyTorch, TensorFlow, Hugging Face Transformers, SpaCy — for building, training, and fine-tuning models
Development Tools and Methodologies:
Git, Agile/Scrum, Jupyter Notebooks for collaborative development and iterative experimentation
Security Protocols:
Knowledge of data privacy, GDPR, and model security best practices for responsible AI deployment
Experience Requirements
Minimum of 6 to 10 years in AI/ML development, with a focus on generative models or NLP
Proven experience training and deploying complex AI models within cloud environments
Demonstrated track record of integrating AI solutions to solve real-world business challenges
Experience working in cross-functional teams, participating in model review and validation processes
Familiarity with AI model governance, ethics, and bias mitigation strategies
Day-to-Day Activities
Develop, train, and fine-tune generative AI models, including language and image models
Collaborate with product and data teams to define AI use cases and develop technical solutions
Conduct model evaluation, performance benchmarking, and iterative improvements
Package and deploy AI models in cloud environments, ensuring scalability and efficiency
Document all processes, including training procedures, model architectures, and deployment steps
Stay current on advancements in Generative AI, NLP, and related fields, recommending new techniques for application
Troubleshoot technical issues and optimize model performance in production environments
Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related field
4+ years of experience in AI/ML development, specifically working with generative models and NLP
Proven expertise in Python, deep learning frameworks, and cloud deployment of AI solutions
Experience with MLOps tools, continuous integration, and model monitoring is a plus
Professional Competencies
Strong analytical and problem-solving skills for developing innovative AI solutions
Excellent communication skills for articulating complex AI concepts to technical and non-technical stakeholders
Self-driven with the ability to independently manage multiple projects and priorities
Willingness to learn new AI techniques, tools, and emerging research
Team-oriented mindset with collaboration skills across diverse technical and business groups
Ability to adapt rapidly to evolving AI research and industry best practices
SYNECHRON’S DIVERSITY & INCLUSION STATEMENT
Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.
All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.
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