Need – AI/ML Engineer – Remote

Hello,

Job Description: AI/ML Engineer

Location: Remote
Role Type: Contract

GC/GC-EAD/USC Only

Rate: $60/hr. on C2C

Position Overview

The candidate will be responsible for designing, developing, and deploying machine learning models and AI-driven solutions to support healthcare analytics, improve operational efficiency, and drive business insights. This role requires strong expertise in machine learning, data engineering, cloud platforms, and end-to-end model lifecycle management.

Key Responsibilities

Develop and implement scalable machine learning models for predictive analytics, classification, NLP, and optimization use cases.
Work closely with data engineers and analysts to gather requirements, understand business problems, and translate them into ML solutions.
Perform data preprocessing, feature engineering, model tuning, and validation.
Build reusable ML pipelines and automate workflows through MLOps frameworks.
Deploy models into production using cloud-native services (Azure, AWS, or GCP).
Monitor and optimize model performance and ensure long-term model stability.
Collaborate cross-functionally with product, engineering, and business stakeholders within Optum.
Document solution designs, model behavior, and deployment architecture.

Mandatory Skills

Strong programming skills in Python (NumPy, Pandas, Scikit-learn, TensorFlow / PyTorch).
Experience building ML models end-to-end, including training, validation, deployment, and monitoring.
Hands-on experience with NLP, LLMs, or generative AI technologies (Hugging Face, LangChain preferred).
Knowledge of cloud platforms such as Azure, AWS, or GCP (Optum widely uses Azure & GCP).
Familiarity with MLOps tools such as MLflow, Kubeflow, Vertex AI, SageMaker, or Azure ML Studio.
Strong understanding of data structures, algorithms, and SQL/NoSQL databases.

Good-to-Have Skills

Experience with deep learning architectures (CNNs, RNNs, Transformers).
Healthcare domain experience (claims, EHR, risk scoring, utilization forecasting).
Exposure to big data technologies (Spark, Databricks, Hadoop).
Experience with API development and microservices for model deployment.
Understanding of responsible AI, bias detection, fairness and model interpretability (SHAP, LIME).

Qualifications

Bachelor’s/Master’s in Computer Science, Data Science, AI/ML, or related field.
3–7+ years of experience in machine learning or AI development.
Strong communication skills and ability to work independently in a remote environment.