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SoftStandard Solutions

Software Engineer

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Summary

SoftStandard Solutions, a US staffing and consulting firm, is hiring a Software Engineer with strong Python and machine learning skills for placement with one of its clients (W2). Day to day the engineer designs, trains, and deploys ML models and production pipelines using TensorFlow/PyTorch, SQL, Docker/Kubernetes, MLOps tooling, and cloud ML platforms.

AI/ML Engineer — Job Description

Contract type: W2


About the Role

Soft Standard Solutions is a leading staffing and consulting firm, specializing in connecting skilled IT professionals with top clients across the US and helping candidates secure strong, long-term placements. We are currently hiring a Software Engineer with good experience in Python development and Machine Learning for one of our esteemed clients. This is a great opportunity for someone who enjoys building scalable software while applying ML techniques to solve real-world problems, with the added support of our placement and career guidance services throughout the process.

Roles & Responsibilities

  • Design, develop, and deploy machine learning models for real-world business use cases
  • Perform data collection, preprocessing, feature engineering, and exploratory data analysis
  • Train, evaluate, and fine-tune ML/DL models for accuracy, performance, and scalability
  • Build and deploy AI/ML pipelines into production environments
  • Work with NLP, Computer Vision, or Generative AI/LLM use cases as applicable
  • Integrate ML models into applications via APIs and microservices
  • Collaborate with data engineers, software developers, and product teams to deliver AI-driven solutions
  • Monitor deployed models for performance, drift, and retraining needs (MLOps)
  • Conduct experiments, A/B testing, and document model performance and findings
  • Stay current with emerging AI/ML trends, tools, and research

Required Skillset

  • Core: Python, Statistics, Data Structures & Algorithms
  • ML/DL Frameworks: TensorFlow, PyTorch, Scikit-learn, Keras
  • Data Handling: Pandas, NumPy, SQL, Data Preprocessing, Feature Engineering
  • Specializations: NLP, Computer Vision, Generative AI/LLMs (as applicable)
  • MLOps & Deployment: MLflow, Docker, Kubernetes, Model Serving (Flask/FastAPI)
  • Cloud Platforms: AWS/Azure/GCP (SageMaker, Azure ML, Vertex AI)
  • Other: Git, Jupyter Notebooks, Agile/Scrum, Model Evaluation Metrics


Skills

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