Remote Machine Learning Engineer – Generative AI & NLP Specialist

Description:

• The Machine Learning Engineer – Generative AI & NLP Specialist will design, develop, and implement cutting-edge AI-driven systems.
• This role will focus on enhancing translation systems using advanced NLP techniques and Generative AI (GenAI).
• The ideal candidate will have extensive experience in end-to-end machine learning (ML) lifecycles and large language models (LLMs).
• The candidate must have the ability to create scalable, secure, and efficient AI solutions.
• Key responsibilities include designing and optimizing translation systems leveraging advanced NLP and GenAI techniques.
• The role involves delivering contextually accurate, multilingual solutions with domain-specific customizations to meet diverse client needs.
• Continuous improvement of performance using metrics like BLEU scores and human evaluation benchmarks is expected.
• The candidate will take ownership of the entire machine learning pipeline, from prototyping and concept validation to scalable production deployment.
• Collaboration with cross-functional teams to align solutions with business objectives and ensure seamless integration is essential.
• Implementing monitoring frameworks to track model performance, detect anomalies, and ensure reliability in production is required.
• The role includes automating pipelines for model retraining and fine-tuning to address data drift and maintain accuracy.
• The candidate will deploy highly scalable inference endpoints that handle concurrent requests efficiently while maintaining low latency.
• Ensuring compliance with security standards, including encryption, access control, and API authentication, is necessary.
• Developing well-documented APIs to enable seamless integration of GenAI capabilities into applications and external systems is part of the job.
• The candidate will support API versioning and updates to meet evolving requirements.
• Working with vector and graph databases to enable efficient Retrieval-Augmented Generation (RAG) systems is expected.
• The role involves optimizing data retrieval processes and evaluating RAG metrics, such as precision and relevance, to ensure high-quality results.

Requirements:

• A deep understanding of the full ML lifecycle, including development, training, deployment, and maintenance, is required.
• Proficiency in tools like Weights & Biases (W&B) or MLflow to track and manage experiments is necessary.
• Strong Python programming skills, with expertise in ML libraries such as LangChain, LlamaIndex, PyTorch, TensorFlow, NumPy, SciPy, pandas, and scikit-learn, are essential.
• Experience designing APIs with industry best practices is required.
• A strong knowledge of large language models, including open-source and commercial implementations, and their practical applications is necessary.
• Basic experience in building or deploying AI agents for specialized tasks is preferred.
• Hands-on experience with vector and graph databases, including understanding metrics for evaluating RAG systems, is required.
• Proficiency in cloud platforms, preferably Google Cloud Platform (GCP), is necessary.
• Familiarity with Docker and containerization technologies is required.
• The candidate must have a proven ability to ensure that GenAI deployments are scalable, secure, and efficient.

Benefits:

• The position offers the opportunity to work on cutting-edge AI technologies and contribute to innovative projects.
• The role allows for remote work flexibility, providing a better work-life balance.
• The candidate will have the chance to collaborate with cross-functional teams and gain exposure to various business objectives.
• There is potential for professional growth and development in the rapidly evolving field of AI and machine learning.
• The position may include competitive compensation and benefits packages, although specific details are not provided.