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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 brand, popular ML title, and broad ML skillset drive high applicant competition.
Core ML engineering skills are transferable, though healthcare and regulated-data experience increases sensitivity.
Moderate technical filters: mandatory programming, ML frameworks, and preferred cloud/MLOps experience.
Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and deploy AI-powered solutions leveraging no-code, low-code, and advanced platforms to enhance products and decision-making.
Develop and maintain production-ready software integrating machine learning models and algorithms across NLP, Computer Vision, Deep Learning, and related technologies.
Collaborate with data scientists, AI researchers, and product teams to operationalize AI/ML models; communicate technical results to stakeholders.
Minimum Requirements
Bachelor's degree in Computer Science, Software Engineering, AI, ML, Data Science, Mathematics, Statistics, or related technical field.
Experience working with SQL and relational databases; proficiency in at least one programming language (Python, Java, or Scala).
Basic understanding of Machine Learning concepts, algorithms, and model evaluation techniques; knowledge of software development lifecycle and source control (Git).
Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Demonstrates ability to develop, test, and deploy machine learning models with guidance, contributing to production-ready AI/ML solutions.
Familiar with cloud platforms (Azure, AWS, GCP), big data technologies (Spark, Hadoop), and MLOps practices including CI/CD pipelines and model monitoring.
Experience or knowledge in healthcare domain or regulated data environments, as well as exposure to advanced AI topics like Generative AI, Large Language Models, and containerization (Docker/Kubernetes).