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
Company H1B Sponsorship