AI/ML Engineer developing intelligent automation solutions using generative AI and machine learning technologies. Ensuring operational efficiency and continuous refinement of integrated AI/ML solutions with a focus on modern engineering.
Responsibilities
The AI/ML Engineer is the architect and guardian of intelligent automation solutions that incorporate generative AI and machine learning technologies.
They ensure the operational efficiency and continuous refinement of integrated AI/ML solutions with a strong focus on modern generative AI engineering.
Your responsibility spans the design, maintenance, and optimization of intelligent automation solutions including AI Center troubleshooting and resolution of issues that might arise post-implementation.
You will focus on building generative AI applications with embedded artificial intelligence or machine learning in support of continuous improvement, learning and augmented decision-making.
Key responsibilities include designing and implementing generative AI solutions using Amazon Bedrock, foundation models, and RAG architectures.
Building repeatable intelligent solutions/bots for document processing and data cleansing.
Developing and deploying scalable ML/AI models on AWS infrastructure.
Creating API endpoints and integrations for AI/ML services.
Implementing model evaluation, monitoring, and continuous improvement processes.
Collaborating with cross-functional teams to embed AI capabilities across business functions.
Requirements
Overall experience of 6-10 Years working on Application/framework development
Min 5+ years of exp in AI/ML-based app/solution development with strong focus on generative AI applications
Hands-on experience with AWS services including Amazon Bedrock, S3, SageMaker, CDK,Lambda, and other AI/ML services
Experience with generative AI models and frameworks (LLMs, RAG architectures, prompt engineering, model fine-tuning)
Hands-on exp with OCR, ICR and OMR technologies is a must
Good programming knowledge in Python and relevant ML/AI frameworks (TensorFlow, PyTorch, LangChain)
Good understanding of Document Processing, classification, data extraction is a must
Knowledge in Natural Language Processing (NLP), Deep Learning, and Generative AI is a must
Hands-on Web application/APIs Development experience is a must
Proficiency in asynchronous/multi-threaded programming
Strong knowledge of algorithms, data structures, complexity, optimization, caching and security
Experience with JSON, SOAP, Rest, XML, XHTML, XSD and XSLT
Strong knowledge of object-oriented concepts and Database concepts
Experience with databases like SQL Server, PostgreSQL
Experience with NoSQL databases and vector databases (for RAG implementations) is a plus
Knowledge of AWS cloud architecture patterns and serverless computing
Experience with CI/CD pipelines and DevSecOps practices
Knowledge of Agile methodologies is desirable
Experience working with a toolchain that includes TFS, SVN, Git
Involved in different phases of SDLC and have good working exposure on different SDLCs like Agile Methodologies
Machine Learning Engineer developing machine learning models for a leading fintech company in Greece. Collaborating with engineering and data teams to enhance decision - making across the financial ecosystem.
MLOps Engineer responsible for managing PyTorch - based training and inference workloads at Menlo HQ. Building and maintaining robust infrastructure for AI models and optimization processes.
Senior Machine Learning Engineer leading ML model development for Adobe's Content Intelligence team. Collaborating with cross - functional teams to enhance creative content understanding using advanced AI.
AI/ML Engineer responsible for designing, building, and operating ML solutions in production. Collaborating with data teams to deliver measurable impact using advanced analytics.
Machine Learning Engineer developing advanced ML - driven applications to enhance quantum technologies. Collaborating with teams to translate complex physical data into actionable improvements.
Lead Machine Learning Engineer at Disney applying AI and machine learning to enhance advertising capabilities. Collaborating with teams to build robust ML systems and drive innovation.
Senior Machine Learning Scientist improving customer and business outcomes using ML and statistical modeling. Working with experienced team and involved in end - to - end model development.
Senior AI/ML Ops Engineer at Smartsheet responsible for building scalable AI/ML platforms. Collaborating with cross - functional teams to enhance data infrastructure and operational efficiency.
Machine Learning Engineer developing LLM - powered systems at Trainline. Designing predictive ML systems, collaborating with cross - functional teams on AI initiatives.