About the Role
Build, train, and deploy machine learning and statistical models to solve high-impact business challenges.
Conduct exploratory data analysis (EDA), data profiling, and feature engineering to support model development.
Work with large-scale structured and unstructured datasets using Python, SQL, PySpark, or similar tools.
Develop and optimize end-to-end ML pipelines for scalability, reliability, and performance.
Apply generative AI, LLMs, and NLP techniques to enhance search, automation, personalization, and predictive capabilities for client solutions.
Collaborate with data engineers to design robust data architectures, including data lakes, data warehouses, and ingestion pipelines.
Partner with product managers and business teams to translate business requirements into analytical solutions and measurable KPIs.
Communicate insights clearly using visualizations, dashboards, and presentations to both technical and non-technical stakeholders.
Stay current with emerging AI/ML research, tools, and frameworks; contribute to internal innovation and best practices.
Requirements
3–6+ years of experience as a Data Scientist or Applied ML Engineer.
Strong programming skills in Python and experience with ML libraries such as scikit-learn, TensorFlow, PyTorch, XGBoost, or equivalent.
Proficiency in SQL and experience working with large datasets across cloud platforms (AWS, Azure, or GCP).
Hands-on experience with NLP, LLMs, or Generative AI models highly preferred.
Experience designing, evaluating, and optimizing supervised, unsupervised, and deep learning models.
Knowledge of MLOps, experimentation frameworks, and versioning tools (MLflow, Weights & Biases, Git, etc.) is a plus.
Strong analytical thinking, problem-solving ability, and communication skills.
Experience working with web, mobile, or SaaS products is advantageous.
About the Company
SierraCorp AI Resources, a division of SierraCorp AI, specializes in delivering client-focused staffing solutions.