We are seeking a hands-on AI / Machine Learning Engineer with experience building and deploying scalable ML solutions in production environments. The ideal candidate has strong expertise in machine learning, data pipelines, and cloud platforms. Key responsibilities include designing, developing, and deploying machine learning models for real-world applications.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
AI / Machine Learning Engineer (6+ Years)
Location: Multiple client locations across USA (Open to relocation)
Employment: Full-time (W2 only, No C2C)
Experience: 6+ Years
🔹 Role Overview
We are seeking a hands-on AI / Machine Learning Engineer with experience building and deploying scalable ML solutions in production environments.
The ideal candidate has strong expertise in machine learning, data pipelines, and cloud platforms, along with exposure to modern AI use cases including NLP and LLM-based applications.
🔹 Key Responsibilities
- Design, develop, and deploy machine learning models for real-world applications
- Build and maintain end-to-end ML pipelines (data ingestion → training → deployment)
- Work with large-scale datasets using Python, SQL, and distributed systems
- Implement ML models into production using APIs, microservices, or batch pipelines
- Collaborate with data engineers and business stakeholders to deliver AI-driven solutions
- Optimize model performance, scalability, and reliability
- Contribute to MLOps practices, including monitoring, retraining, and versioning
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🔹 Required Skills
Core ML & Programming
- Python (NumPy, Pandas, Scikit-learn)
- Strong SQL skills
- Solid understanding of ML algorithms (classification, regression, clustering)
Advanced / AI
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- Experience with NLP or deep learning (TensorFlow / PyTorch)
- Exposure to LLMs / Generative AI use cases (prompting, embeddings, APIs)
Data & Engineering
- Experience with Spark / PySpark (preferred)
- Data pipeline development (ETL/ELT)
Cloud & Deployment
- AWS / Azure / GCP
- Experience deploying models using REST APIs or microservices
- Familiarity with Docker / containerization
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🔹 Nice to Have
- Experience with MLOps tools (MLflow, SageMaker, Vertex AI, etc.)
- Airflow or workflow orchestration tools
- Experience with real-time or streaming ML systems
- Knowledge of feature stores and model monitoring
🔹 Why Join
- Work on modern AI/ML and data-driven projects
- Exposure to enterprise-scale implementations
- Collaborative and innovation-focused environment
- Long-term opportunities with top clients
📩 Apply: rajesh@precisiontechcorp.com
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