Job Summary
Synechron is seeking a highly skilled AI/ML Engineer specializing in Generative AI, Large Language Models (LLMs), and agentic AI solutions. The successful candidate will lead end-to-end model development, including designing, training, optimizing, and deploying advanced AI models with a focus on GCP (BigQuery). This role drives innovation by integrating cutting-edge AI technologies into scalable, production-ready systems, supporting the organization's digital transformation and AI strategy.
Software Requirements
- Required:
- Python (expert level; version 3.8+) for model building and pipelines
- Java (proficiency) for integrating models into enterprise systems
- SQL (including BigQuery) and NoSQL databases for data processing
- Deep learning frameworks: TensorFlow, PyTorch, Keras
- Version control: Git
- MLOps tools: MLFlow, experiment tracking, and model registry tools
- Preferred:
- Docker, Kubernetes for containerized deployment
- API development frameworks such as FastAPI, Flask, or Spring Boot
- Vector database tools like FAISS, Pinecone, Chroma
Overall Responsibilities
- Lead the development of large-scale, high-performance ML and LLM models, including prompt engineering and fine-tuning.
- Design and implement Retrieval-Augmented Generation (RAG) pipelines to enhance contextual accuracy.
- Convert models into scalable APIs or microservices to facilitate enterprise deployment.
- Optimize models for latency, throughput, and cost-efficiency in production environments.
- Build reusable ML codebases, data pipelines, and features for ongoing model training and inference.
- Collaborate with cross-team data engineers, product managers, and cloud specialists to embed AI solutions into organizational systems.
- Conduct research on emerging AI advancements, benchmark technologies, and recommend adoption strategies.
Technical Skills (By Category)
- Programming Languages: Required: Python (expert, 3.8+), Java (proficient) Preferred: Additional scripting languages (e.g., Bash, JavaScript)
- Databases/Data Management: BigQuery, NoSQL options (MongoDB, Firebase) data querying, feature engineering, and data pipeline design
- Cloud Technologies: Google Cloud Platform (BigQuery, Vertex AI), with experience deploying ML models at scale
- Frameworks and Libraries: TensorFlow, PyTorch, Keras, DataWeave, FastAPI or Flask for API deployment
- Development Tools and Methodologies: Git, MLFlow, CI/CD pipelines, containerization via Docker/Kubernetes, Agile methods
- Security Protocols: Understanding of data privacy, model security, and enterprise compliance standards
Experience Requirements
- Minimum of 3 years of experience developing and deploying ML models, with at least 1 year dedicated to LLMs and generative AI.
- Proven track record in building, fine-tuning, and deploying RAG architectures and agentic AI workflows.
- Hands-on experience working with GCP services, especially BigQuery, Vertex AI, and cloud-based ML workflows.
- Demonstrated success in integrating AI models into production environments and enterprise systems.
- Experience in driven data pipelines, feature engineering, and model optimization in cloud environments.
- Industry experience in technology, finance, or enterprise software sectors is advantageous.
Day-to-Day Activities
- Design, develop, and validate advanced AI and language models, including prompt engineering and fine-tuning.
- Manage RAG pipelines and integrate models into scalable APIs and microservices.
- Collaborate with data engineers, software developers, and product teams to embed AI solutions across platforms.
- Implement model monitoring, performance tuning, and cost optimization strategies.
- Conduct experiment tracking, documentation, and knowledge sharing through MLFlow or related tools.
- Keep current with emerging AI research, benchmarking new techniques, and integrating innovations.
Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, or related field.
- Professional certifications in AI/ML (e.g., Google Cloud Professional Data Engineer, TensorFlow Developer) are preferred.
- Commitment to continuous learning through workshops, certifications, or conference participation.
- Proven experience working on enterprise-grade AI projects in cloud environments.
Professional Competencies
- Strong analytical and problem-solving skills for complex model development and deployment.
- Excellent communication skills to articulate technical concepts to non-technical stakeholders.
- Leadership qualities to guide project efforts and mentor junior team members.
- Ability to adapt to rapidly evolving AI technologies and project priorities.
- Innovation-driven with a strategic mindset focused on scalable, sustainable AI systems.
- Organizational skills to manage multiple experiments, models, and deployment tasks effectively.
S YNECHRON'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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