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Junior Ai Machine Learning Python Jobs in Pennsylvania

Gather AI

Director of Machine Learning

Pittsburgh, PA · On-site

Gather AI is pioneering a new era of warehouse intelligence with innovative software that utilizes ... Python and PyTorch (or TensorFlow) proficiency, plus a track record of shipping ML models to ...

Gather AI

Director of Machine Learning

Pittsburgh, PA · On-site

At Gather AI, we're not just creating software; we're pioneering a new era of warehouse ... Strong Python and PyTorch (or TensorFlow) proficiency, plus a track record of shipping ML models to ...

Gather AI

Director of Machine Learning

Pittsburgh, PA · On-site +1

At Gather AI, we're not just creating software; we're pioneering a new era of warehouse ... Strong Python and PyTorch (or TensorFlow) proficiency, plus a track record of shipping ML models to ...

Gather AI

Director of Machine Learning

Pittsburgh, PA · On-site

At Gather AI, we're not just creating software; we're pioneering a new era of warehouse ... Strong Python and PyTorch (or TensorFlow) proficiency, plus a track record of shipping ML models to ...

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Junior Ai Machine Learning Python information

What are the key skills and qualifications needed to thrive as a junior AI machine learning Python engineer, and why are they important?

To thrive as a Junior AI Machine Learning Python Engineer, you need a solid understanding of Python programming, statistics, and foundational machine learning concepts, often supported by a degree in computer science or a related field. Familiarity with tools and frameworks like TensorFlow, Scikit-learn, Jupyter Notebooks, and version control systems such as Git is typically required. Strong problem-solving abilities, attention to detail, and effective teamwork skills help individuals excel in collaborative and fast-evolving technical environments. These competencies are crucial for developing robust AI solutions, learning from senior colleagues, and adapting to the rapidly changing landscape of machine learning.

What does a junior AI machine learning Python engineer do?

A Junior AI Machine Learning Python engineer assists in developing, testing, and maintaining machine learning models using Python. They typically work with data preparation, preprocessing, and applying basic algorithms to solve real-world problems. Under the guidance of senior engineers, they help implement solutions, evaluate model performance, and may contribute to the deployment of models into production environments. Their role often includes learning best practices in coding, software development, and collaborating with data scientists and engineers.

What are some typical projects or tasks a junior AI machine learning Python developer might work on in their first year?

As a Junior AI/Machine Learning Python developer, you can expect to work on tasks such as cleaning and preparing datasets, developing and testing simple machine learning models, and assisting in the implementation of algorithms under the supervision of senior team members. You may also help automate data pipelines, write scripts for data extraction, and contribute to model evaluation and reporting. Collaboration with data scientists, software engineers, and product managers is common, providing valuable learning opportunities and exposure to the full machine learning workflow.

What is the difference between Junior Ai Machine Learning Python vs Data Analyst?

AspectJunior Ai Machine Learning PythonData Analyst
Required SkillsPython, Machine Learning, AI concepts, data preprocessingExcel, SQL, data visualization, basic statistical analysis
CertificationsPython certifications, AI/ML coursesData analysis or visualization certifications
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, marketing departments
Industry UsageDeveloping AI models, machine learning pipelinesInterpreting data, generating reports, supporting decision-making

Junior Ai Machine Learning Python roles focus on developing AI models using Python and machine learning techniques, often in tech-driven environments. Data Analysts primarily interpret data, create visualizations, and support business decisions. While both roles require analytical skills, AI/ML roles demand programming and AI-specific knowledge, whereas Data Analysts focus on data interpretation and reporting.

What are popular job titles related to Junior Ai Machine Learning Python jobs in Pennsylvania? For Junior Ai Machine Learning Python jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Junior Ai Machine Learning Python jobs in Pennsylvania look for? The top searched job categories for Junior Ai Machine Learning Python jobs in Pennsylvania are:
What cities in Pennsylvania are hiring for Junior Ai Machine Learning Python jobs? Cities in Pennsylvania with the most Junior Ai Machine Learning Python job openings:
Junior Ai Machine Learning Python jobs near you

Principal Machine Learning Engineer[W2 ROLE]

SmartIPlace

Philadelphia, PA • On-site

Contractor

Posted 20 days ago

Job description

Title: Principal Machine Learning Engineer

Location: Philadelphia, PA (Hybrid – Onsite Tuesdays & Wednesdays)
Duration: 6+ Months Contract-to-Hire
Employment Type: W2
Work Authorization: Must be authorized to work in the U.S.

Job Summary

Medical Guardian is seeking a Principal Machine Learning Engineer to lead the design, development, deployment, and optimization of machine learning solutions supporting predictive analytics, scoring, decision intelligence, and AI-driven automation. This is a hands-on technical leadership role focused on building production-ready ML models while partnering with stakeholders to solve complex business problems.

Key Responsibilities
  • Design, build, validate, and deploy machine learning models for prediction, scoring, risk detection, prioritization, and decision support.
  • Perform exploratory data analysis (EDA), feature engineering, model training, tuning, validation, and performance evaluation.
  • Develop scalable ML pipelines using Python, SQL, Spark, Databricks, MLflow, scikit-learn, XGBoost, and similar technologies.
  • Build reusable feature engineering frameworks and model-ready datasets.
  • Monitor production models for performance, drift, calibration, retraining, and lifecycle management.
  • Collaborate with business and technical stakeholders to translate business challenges into ML solutions.
  • Ensure models are explainable, maintainable, and production-ready.
  • Follow software engineering best practices including version control, testing, documentation, and code quality.
  • Provide technical leadership and guidance on AI/ML best practices and model design.
Required Qualifications
  • 5+ years of hands-on experience in machine learning model development.
  • 3+ years of experience deploying and supporting machine learning models in production environments.
  • Strong programming experience with Python and SQL.
  • Experience with Databricks, Apache Spark, MLflow, Snowflake, Azure, AWS, or similar cloud/data platforms.
  • Strong understanding of feature engineering, model evaluation, model monitoring, drift detection, calibration, thresholding, and retraining.
  • Experience developing predictive models, scorecards, and decision-support systems.
  • Ability to communicate technical concepts effectively to both technical and non-technical stakeholders.
  • Strong software engineering practices including testing, documentation, reproducibility, and maintainable code.
Preferred Qualifications
  • Experience with Generative AI and AI automation.
  • Knowledge of MLOps and production machine learning lifecycle management.
  • Experience with explainable AI (XAI) and transparent modeling techniques.
  • Background in predictive analytics, customer engagement, or risk modeling.
  • Experience working in Agile environments.
Required Skills
  • Machine Learning
  • Python
  • SQL
  • Databricks
  • Apache Spark
  • MLflow
  • scikit-learn
  • XGBoost
  • Snowflake
  • Azure / AWS
  • Feature Engineering
  • Predictive Modeling
  • Model Deployment
  • MLOps
  • Generative AI
  • AI Automation
  • Model Monitoring
  • Stakeholder Management
Smart-iPlace logo

About Smart-iPlace

Sourced by ZipRecruiter

SMART-iPLACE provides innovative staffing and consulting solutions that help our clients achieve their business objectives. We can understand and support all areas of your IT systems from back-end infrastructure to front-end personal productivity. Our goal is create innovative IT solutions that enable your business to be more agile and competitive.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Irving, TX, US

Year founded

2021

Social media

Facebook

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