AIML Engineer

Raas Infotek; Texas City (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

Raas Infotek (USA) seeks a Senior AI/ML Engineer with 12+ years of experience in software engineering, ML/AI, and data-driven apps. You will design, deploy, and maintain ML solutions, collaborating with data scientists, software engineers, product teams, and business stakeholders.

You will work on NLP, generative AI, LLMs, and prompt engineering, plus cloud-based ML deployments using AWS/Azure/GCP, Docker/Kubernetes, and CI/CD. Strong communication and SDLC knowledge are essential.

Qualifications

• 12+ years of experience in software engineering, data science, AI/ML, or related technologies.
• Strong Python programming experience.
• Solid understanding of ML algorithms, statistics, and predictive modeling.
• Hands-on with TensorFlow and/or PyTorch.
• Experience with NLP, generative AI, LLMs, and prompt engineering.
• Familiar with RAG, embeddings, vector databases, and semantic search.
• Experience with SQL and NoSQL databases.
• REST APIs and microservices for integrating ML models.
• Hands-on with AWS, Azure, or GCP; Docker and Kubernetes; CI/CD.
• Knowledge of MLOps, model deployment and lifecycle management.
• Strong Git, Agile/Scrum, and SDLC understanding.

Responsibilities

• Design, develop, and deploy ML/AI solutions for business needs.
• Build and optimize predictive and classification models.
• Develop data processing and feature pipelines using Python.
• Train, evaluate, and tune ML models.
• Develop NLP and Generative AI solutions for business use cases.
• Work with LLMs, embeddings, vector databases, and RAG-based apps.
• Integrate ML models into enterprise apps via APIs and microservices.
• Deploy and manage ML models in cloud environments.
• Build and maintain MLOps pipelines for training, deployment, monitoring, retraining.

Skills

Python

ML algorithms

Deep learning

NLP

Generative AI

LLMs

Prompt engineering

RAG

Embeddings

SQL

NoSQL

REST APIs

Microservices

AWS

Azure

GCP

Docker

Kubernetes

CI/CD

MLOps

Git

Agile/Scrum

SDLC

Tools

Scikit-learn

Pandas

NumPy

TensorFlow

PyTorch

Spark

PySpark

FastAPI

Flask

PostgreSQL

MySQL

MongoDB

Redis

Pinecone

FAISS

Weaviate

Milvus

Job description

Job Description

We are looking for an experienced AI/ML Engineer with 12+ years of experience in software engineering, machine learning, artificial intelligence, and data-driven application development. The ideal candidate should have strong hands‑on experience with Python, machine learning algorithms, deep learning, NLP, generative AI, and cloud-based ML solutions.

Senior AI/ML Engineer

Experience: 12+ Years

We are looking for an experienced AI/ML Engineer with 12+ years of experience in software engineering, machine learning, artificial intelligence, and data-driven application development. The ideal candidate should have strong hands‑on experience with Python, machine learning algorithms, deep learning, NLP, generative AI, and cloud-based ML solutions.

The candidate will be responsible for developing, deploying, and maintaining machine learning solutions and working closely with data scientists, software engineers, product teams, and business stakeholders.

Required Skills

• 12+ years of experience in software engineering, data science, AI/ML, or related technologies.
• Strong programming experience with Python.
• Strong understanding of Machine Learning algorithms, statistics, and predictive modeling.
• Experience with Scikit-learn, Pandas, NumPy, and ML frameworks.
• Hands‑on experience with TensorFlow and/or PyTorch.
• Experience developing and deploying Machine Learning models.
• Strong understanding of NLP, text processing, classification, regression, clustering, and recommendation systems.
• Experience with Generative AI, Large Language Models (LLMs), and prompt engineering.
• Knowledge of RAG, embeddings, vector databases, and semantic search.
• Experience working with SQL and NoSQL databases.
• Experience with REST APIs and microservices for integrating ML models with applications.
• Hands‑on experience with AWS, Azure, or Google Cloud Platform.
• Experience with Docker, Kubernetes, and CI/CD.
• Knowledge of MLOps, model deployment, monitoring, and model lifecycle management.
• Strong understanding of Git, Agile/Scrum, and SDLC.

Responsibilities

• Design, develop, and deploy machine learning and AI solutions for business requirements.
• Build and optimize predictive and classification models using appropriate ML algorithms.
• Develop data processing and feature engineering pipelines using Python.
• Train, evaluate, validate, and tune machine learning models.
• Develop NLP and Generative AI solutions based on business use cases.
• Work with LLMs, embeddings, vector databases, and RAG-based applications.
• Integrate AI/ML models into enterprise applications using APIs and microservices.
• Deploy and manage ML models in cloud environments.
• Build and maintain MLOps pipelines for model training, deployment, monitoring, and retraining.
• Monitor model performance and address issues related to accuracy, scalability, and reliability.
• Work with data engineers to prepare and transform data required for ML solutions.
• Collaborate with data scientists, software engineers, architects, and product teams.
• Perform code reviews and follow software engineering best practices.
• Troubleshoot production issues and provide root‑cause analysis.
• Document technical solutions, model approaches, and deployment processes.
• Mentor junior engineers and provide technical guidance to the team.

Technical Environment

Programming: Python, SQL

ML: Scikit-learn, Pandas, NumPy

Deep Learning: TensorFlow, PyTorch

AI/GenAI: LLMs, NLP, RAG, Prompt Engineering, Embeddings

Databases: PostgreSQL, MySQL, MongoDB, Redis

Vector Databases: Pinecone, FAISS, Weaviate, Milvus

Cloud: AWS, Azure, Google Cloud Platform

DevOps/MLOps: Docker, Kubernetes, Git, Jenkins, CI/CD

APIs: REST, FastAPI, Flask

Data Processing: Spark, PySpark, ETL/ELT

Preferred Skills

• Experience with OpenAI, Azure OpenAI, or other LLM platforms.
• Experience building RAG and agent-based AI applications.
• Knowledge of LangChain or LlamaIndex.
• Experience with ML platforms such as AWS SageMaker, Azure ML, or Vertex AI.
• Knowledge of model serving technologies and ML monitoring.
• Experience with distributed computing and big data technologies.
• Experience with cloud-native application development.
• Strong understanding of AI/ML security, data privacy, and responsible AI practices.
• Experience in Banking, Healthcare, Insurance, Retail, or other enterprise domains.