Senior AI/Machine Learning Engineer

Good co India; Singapore; On-site; SGD 120,000 - 170,000; Full time

Job summary

Good co India seeks an experienced AI/ML Engineer to design, develop, and deploy scalable AI/ML solutions for production systems. You will build and optimize ML/DL and Generative AI models, including LLMs, with prompt engineering, RAG, AI agents, and vector databases.

You will design data pipelines, feature engineering workflows, and model training processes, and deploy models using MLOps. You will collaborate with product, software, and data teams to translate business needs into AI-driven

Qualifications

• 5 to 10 years of experience in AI, ML, DS, or related fields.
• Bachelor's or Master's in CS/AI/DS/Math/Stats or related discipline.
• Strong Python and ML framework experience (PyTorch, TensorFlow, Scikit-learn, Hugging Face).
• Proven production-grade ML/Gen AI app experience.
• Hands-on with LLMs, Prompt Engineering, RAG, AI Agents, LangChain, LlamaIndex, and vector databases.
• Cloud experience (AWS/Azure/GCP) and MLOps tools (Docker, Kubernetes, MLflow, Kubeflow).
• Solid ML/NLP knowledge and model optimization skills.
• REST APIs, microservices, and scalable distributed systems.
• Strong analytical, communication, and stakeholder management.

Responsibilities

• Design, develop, deploy, and maintain scalable AI/ML solutions for production environments.
• Build, fine-tune, and optimize ML, DL, and Generative AI models to solve complex business problems.
• Develop and implement LLM applications using prompt engineering, RAG, AI agents, and vector databases.
• Design and optimize data pipelines, feature engineering workflows, and model training processes.
• Deploy and manage ML models using MLOps best practices, ensuring scalability, reliability, and performance.
• Collaborate with product managers, software engineers, data engineers, and stakeholders to translate requirements into AI-driven solutions.
• Evaluate model performance, conduct A/B testing, monitor production models, and implement improvements.
• Develop APIs and integrate AI/ML models into enterprise applications and cloud-based systems.
• Ensure AI solutions adhere to security, governance, explainability, and responsible AI standards.
• Mentor junior engineers, conduct code reviews, and promote engineering best practices.
• Stay current with advancements in AI, ML, and Generative AI technologies and recommend innovations.

Skills

Python

PyTorch

TensorFlow

Scikit-learn

Hugging Face

LLMs

Prompt Engineering

RAG

AI Agents

LangChain

LlamaIndex

vector databases

AWS

Azure

GCP

Docker

Kubernetes

MLflow

Kubeflow

REST APIs

Microservices

Distributed systems

Education

Bachelor's or Master's degree in Computer Science, AI, Data Science, Mathematics, Statistics, or related discipline

Tools

Docker

Kubernetes

MLflow

Kubeflow

LangChain

LlamaIndex

vector databases

Job description

Role & responsibilities

• Design, develop, deploy, and maintain scalable AI/ML solutions for production environments.
• Build, fine-tune, and optimize machine learning, deep learning, and Generative AI models to solve complex business problems.
• Develop and implement Large Language Model (LLM) applications using prompt engineering, Retrieval-Augmented Generation (RAG), AI agents, and vector databases.
• Design and optimize data pipelines, feature engineering workflows, and model training processes.
• Deploy and manage ML models using MLOps best practices, ensuring scalability, reliability, and performance.
• Collaborate with product managers, software engineers, data engineers, and business stakeholders to translate business requirements into AI-driven solutions.
• Evaluate model performance, conduct A/B testing, monitor production models, and implement continuous improvements.
• Develop APIs and integrate AI/ML models into enterprise applications and cloud-based systems.
• Ensure AI solutions adhere to security, governance, explainability, and responsible AI standards.
• Mentor junior engineers, conduct code reviews, and promote engineering best practices.
• Stay current with advancements in AI, machine learning, and Generative AI technologies and recommend innovative solutions.

Preferred candidate profile

• 5 to 10 years of experience in AI, Machine Learning, Data Science, or related fields.
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, Statistics, or a related discipline.
• Strong hands-on experience with Python and AI/ML frameworks such as PyTorch, TensorFlow, Scikit-learn, and Hugging Face.
• Proven experience building and deploying production-grade machine learning and Generative AI applications.
• Hands-on experience with LLMs, Prompt Engineering, RAG, AI Agents, LangChain, LlamaIndex, and vector databases.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform and MLOps tools including Docker, Kubernetes, MLflow, or Kubeflow.
• Strong understanding of machine learning algorithms, deep learning, NLP, and model optimization techniques.
• Experience developing REST APIs, microservices, and scalable distributed systems.
• Excellent analytical, problem-solving, communication, and stakeholder management skills.
• Ability to work independently in a fast-paced, collaborative environment and lead technical initiatives.
• Experience mentoring team members and driving technical excellence is highly desirable.