Generative AI ML/LLM Engineer SR

Job Summary

As an AI Engineer, you will be designing, developing, and implementing machine learning algorithms and models for various applications, with a focus on natural language processing and understanding. In this journey, you will have opportunity to perform data preparation, model training and optimization, integration of machine learning models into production systems, as well as evaluating, testing and documenting machine learning models.

Responsibilities and Duties

• Algorithm Development: Design, develop, and implement machine learning algorithms and models for various applications, with a focus on natural language processing and understanding;
  
• Data Preparation: Collect, preprocess, and clean large datasets to train and validate machine learning models. Collaborate with data engineers to ensure data quality and accessibility;
  
• Model Training and Optimization: Train, fine-tune, and optimize machine learning models for performance, accuracy, and scalability. Stay abreast of the latest advancements in machine learning and implement best practices;
  
• Integration: Collaborate with software engineers and product teams to integrate machine learning models into production systems. Ensure seamless deployment and monitor model performance in real-world scenarios;
  
• Evaluation and Testing: Develop rigorous testing procedures to evaluate the performance and robustness of machine learning models. Conduct experiments to optimize and improve model outcomes;
  
• Documentation: Create comprehensive documentation for machine learning models, including model architecture, training methodologies, and deployment procedures. Facilitate knowledge transfer within the team;
  
• Collaboration: Work closely with cross-functional teams, including data scientists, software engineers, and product managers, to understand business requirements and contribute to the overall success of projects;
  
• Research: Stay informed about the latest advancements in machine learning, natural language processing, and related fields. Apply cutting-edge research to solve business challenges.

Essential Skills

• Proven experience in developing and deploying machine learning models, with a focus on natural language processing;
  
• Proficiency in programming languages such as Python, and experience with machine learning frameworks (e.g., TensorFlow, PyTorch);
  
• Strong understanding of data structures, algorithms, and statistical modeling;
  
• Solid understanding of software engineering principles and best practices;
  
• Experience with large language models and deep learning architectures;
  
• Proven expertise in building RAG-based LLMs applications;
  
• Proficiency with Python and experience with deep learning frameworks like JAX, Keras, PyTorch, or TensorFlow;
  
• Proficiency with generative AI libraries such as Hugging Face, LangChain, and OpenAI;
  
• Proficiency with vector databases like ChromaDB, Pinecone, and Weaviate;
  
• Proven experience designing and building cloud-based machine learning applications in either AWS, Azure, or Google Cloud.

Highly Desirable Skills

• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud);
  
• Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes);
  
• Familiarity with big data technologies (e.g., Apache Spark);
  
• Previous experience in deploying machine learning models in production environments.

About Encora

Encora is the preferred digital engineering and modernization partner of some of the world’s leading enterprises and digital native companies. With over 9,000 experts in 47+ offices and innovation labs worldwide, Encora’s technology practices include Product Engineering & Development, Cloud Services, Quality Engineering, DevSecOps, Data & Analytics, Digital Experience, Cybersecurity, and AI & LLM Engineering.

At Encora, we hire professionals based solely on their skills and qualifications, and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.