[Remote] AI/ML Engineer

Note: The job is a remote job and is open to candidates in USA. SoftStandard Solutions is seeking an experienced AI/ML Engineer to design, develop, train, and deploy machine learning and artificial intelligence solutions. The role focuses on building ML pipelines and AI/ML applications, implementing MLOps workflows, integrating models into production, and collaborating with technical and business teams.

Responsibilities

• Design, develop, train, and deploy machine learning and deep learning models
• Build and optimize ML pipelines for data preparation, feature engineering, model training, and evaluation
• Work with NLP, Generative AI, LLMs, RAG, embeddings, and vector databases where applicable
• Develop AI/ML applications using Python, TensorFlow, PyTorch, or Scikit-learn
• Implement and maintain MLOps workflows , including model deployment, monitoring, versioning, and retraining
• Work with cloud platforms such as AWS, Azure, or GCP for AI/ML development and deployment
• Collaborate with Data Engineers, Software Engineers, Product Managers, and business teams
• Perform model evaluation, hyperparameter tuning, experimentation, and performance optimization
• Build scalable APIs and integrate ML models into production applications
• Ensure models meet requirements for accuracy, scalability, reliability, and responsible AI

Skills

• 4–5 years of professional experience in AI/ML, Machine Learning Engineering, or a related field
• Strong programming skills in Python
• Hands-on experience with Scikit-learn, TensorFlow, PyTorch, or Keras
• Strong understanding of ML algorithms, statistics, feature engineering, model evaluation, and optimization
• Knowledge of SQL, REST APIs, Docker, Kubernetes, Git, and CI/CD
• Experience with at least one cloud platform: AWS, Microsoft Azure, or Google Cloud
• Strong understanding of data structures, algorithms, and software engineering best practices
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Mathematics, or a related field
• Equivalent practical experience may be considered
• Experience with NLP, Generative AI, LLMs, RAG, prompt engineering, and embeddings
• Experience with Hugging Face, LangChain/LangGraph, OpenAI/Azure OpenAI, or similar AI frameworks
• Familiarity with MLflow, Kubeflow, SageMaker, Azure ML, or Vertex AI
• Candidates should ideally hold any one of the mentioned certifications
• AWS Certified Machine Learning Engineer – Associate
• Microsoft Certified: Azure AI Engineer Associate (AI-102)
• Google Cloud Professional Machine Learning Engineer

Company Overview

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