Job Title: Machine Learning Engineer Company Name: Data Capital Incorporation Job Url: https://jobright.ai/jobs/info/696fa7e70f4e0f657ea3ebad Job Description: Data Capital Incorporation ยท 1 month ago Machine Learning Engineer United States Full-time Remote Senior Level 5+ years exp 67% FAIR MATCH 64% Exp. Level 42% Skill 46% Industry Exp. Maximize your interview chances Data Capital Incorporation is seeking a Machine Learning Engineer to develop and implement machine learning models. The role involves collaborating with data scientists, optimizing ML pipelines, and deploying models using cloud services. Information Technology & Services H1B Sponsor Likely Hiring Manager Srinivas Anepalli Insider Connection @Data Capital Incorporation 2 email credits available today Discover valuable connections within the company who might provide insights and potential referrals. Get 3x more responses when you reach out via email instead of LinkedIn. Beyond Your Network S Srinivas Anepalli Recruiter From Your Previous Company F F F & 2 connections Previously@undefined and... From Your School F F F & 2 connections @undefined and... Find Any Email Responsibilities Collaborate with data scientists and SMEs to develop ML models using curated datasets Conduct experiments, prototypes, and proof-of-concepts to validate model performance Create scalable and reusable training pipelines using Databricks notebooks and MLflow Operationalize models with robust CI/CD workflows Deploy models using MLflow, SageMaker, or custom APIs Monitor production models for accuracy, drift, and latency; manage retraining schedules Work closely with Data Engineering to align ML pipelines with the Bronze, Silver, Gold layers of a Medallion Architecture Engineer high-quality features and maintain training/inference pipelines Leverage AWS services including S3, EC2, Lambda, SageMaker, and Step Functions Document ML artifacts, processes, and performance outcomes Contribute to agile project ceremonies and maintain a feedback loop with stakeholders Share knowledge and mentor junior team members Qualification Represents the skills you have Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise. Machine Learning Engineering Python MLOps AWS Databricks ML libraries Mathematics Statistics Software Engineering Principles Communication Teamwork Required 5+ years of experience in ML Engineering or Applied Machine Learning Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow) Proficient with Databricks, MLflow, and PySpark Solid understanding of model lifecycle and MLOps practices Experience with AWS-based data infrastructure and related DevOps practices Demonstrated ability to productionize models and integrate with business system Strong understanding of mathematics and statistics relevant to machine learning and AI Proven experience with machine learning models and algorithms (supervised, unsupervised, deep learning, etc.) Solid background in software engineering principles and best practices Hands-on experience with model training frameworks (e.g., TensorFlow, PyTorch, Hugging Face) Experience with MLOps tools and workflows, particularly on AWS (SageMaker, Lambda, S3, etc.) Practical experience with LLMs, RAGs, and AI agent architectures Proficiency with the Databricks platform for data engineering and ML pipelines Advanced programming skills in Python Excellent communication and teamwork abilities Preferred Experience building and deploying interactive UIs for AI models using Streamlit, Gradio, or similar frameworks for rapid prototyping and real-time model interactions Business acumen and ability to align AI solutions with organizational goals Optimize compute and storage resources for performance and cost-efficiency Company