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Senior Bioinformatics Machine Learning Jobs in Pennsylvania

Machine Learning Engineer III

Pittsburgh, PA · On-site

$111K - $133K/yr

They are seeking a Senior Machine Learning Engineer to develop and optimize machine learning models aimed at enhancing patient care and operational efficiency in hospital settings. Responsibilities ...

Showing results 21-40

Senior Bioinformatics Machine Learning information

What is the difference between Senior Bioinformatics Machine Learning vs Bioinformatics Data Analyst?

AspectSenior Bioinformatics Machine LearningBioinformatics Data Analyst
Required CredentialsAdvanced degrees in bioinformatics, computer science, or related fields; experience with machine learningBachelor's or master's in bioinformatics, biology, or related fields; proficiency in data analysis tools
Work EnvironmentResearch labs, biotech companies, or pharma; focus on developing ML modelsData interpretation, reporting, and visualization in research or clinical settings
Employer & Industry UsageUsed in biotech, pharma, research institutions for complex data modelingCommon in healthcare, research, and biotech for data management and reporting

The main difference is that Senior Bioinformatics Machine Learning specialists focus on developing and applying machine learning models to biological data, requiring advanced technical skills. Bioinformatics Data Analysts primarily interpret and visualize data, with less emphasis on machine learning techniques.

What are popular job titles related to Senior Bioinformatics Machine Learning jobs in Pennsylvania?

For Senior Bioinformatics Machine Learning jobs in Pennsylvania, the most frequently searched job titles are:

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The top searched job categories for Senior Bioinformatics Machine Learning jobs in Pennsylvania are:

Principal Machine Learning Engineer

RIT Solutions, Inc.

Philadelphia, PA • On-site

Full-time

Re-posted 20 days ago


Job description

Job Summary:
RIT Solutions, Inc. is seeking a Principal Machine Learning Engineer to serve as a hands-on technical leader for machine learning initiatives. This role will focus on building, validating, deploying, and improving machine learning models while engaging with stakeholders and ensuring production readiness.
Responsibilities:
• Build, test, validate, and improve machine learning models for scoring, prediction, prioritization, risk detection, engagement, intervention targeting, and decision support.
• Perform exploratory data analysis, data quality assessment, feature engineering, model training, model selection, and performance evaluation.
• Develop practical ML models that balance predictive performance, explainability, stability, maintainability, and business usefulness.
• Work with structured, semi-structured, and operational data to create model-ready datasets and reusable features.
• Use tools such as Python, SQL, Spark, Databricks, MLflow, scikit-learn, XGBoost, or similar platforms and libraries.
• Move quickly from data exploration to prototype to validated model to production-ready capability.
Qualifications:
Required:
• Professional experience in machine learning, data science, software engineering, analytics engineering, applied AI, or related technical fields.
• 5+ years of hands-on machine learning model development experience, including feature engineering, model training, validation, evaluation, and iteration.
• 3+ years of experience deploying, operationalizing, or supporting models in production or business-critical environments.
• Strong hands-on experience with Python and SQL.
• Experience with modern ML and data platforms such as Databricks, Spark, MLflow, Snowflake, Azure, AWS, or similar technologies.
• Strong understanding of model evaluation, calibration, thresholding, score interpretation, monitoring, drift, retraining, and production ML lifecycle management.
• Experience translating ambiguous business problems into concrete ML designs, model requirements, validation plans, and measurable outcomes.
• Ability to explain model behavior, model performance, assumptions, limitations, and tradeoffs to both technical and non-technical stakeholders.
• Strong engineering discipline, including clean code, reproducibility, versioning, testing, documentation, and maintainability.
• Ability to work independently as a senior hands-on contributor while also providing technical leadership and modeling judgment.
Company:
Jobdiva Job Portal: https://www1.jobdiva.com/candidates/myjobs/searchjobsdone.jsp?a=xbjdnwgjodtga1y1im2g881fkkeiwd0775lbvq8yqgps8vb2q36w2vj1ga6xxork&compid=-1 Recruitment (contingency search and campus selection). Founded in 2019, the company is headquartered in Arlington, USA, with a team of 201-500 employees. The company is currently Growth Stage.