Machine Learning Engineer

1 month ago

philadelphia, United States Graphite GTC Full time

Since our inception in 2017, Graphite GTC has been on a mission to redefine the landscape of software development. Our groundbreaking No-Code development platform has transformed the way software is conceived and created, democratizing the process and making it accessible to all. Our mantra, “Better. Faster. Cheaper.™” is not just a slogan; it's the reality we deliver through our innovative platform.


At Graphite GTC, we are not just a technology company; we are a beacon of innovation in the no-code application development sphere. Our vision is to provide equal access to cutting-edge technology for a diverse range of clients, from sprightly startups to established enterprises. We achieve this vision by moving away from traditional hand-coding methods and embracing a visually driven approach to application design, enabling anyone to craft sustainable, enterprise-class applications. Our proprietary software stands as a testament to our innovative spirit and technical prowess. This intellectual property has not only set us apart in the market but has also been the cornerstone of our service offerings. We have evolved into a full-service IT and consulting powerhouse, catering to an impressive roster of clients including the U.S. government, leading pharmaceutical companies, educational institutions, and giants in the construction and sustainability sectors.


Our team is a melting pot of experienced professionals and vibrant technologists, all united by a shared passion for innovation. We foster a culture where humor meets humility, creativity intersects with collaboration, and where problem-solving happens at the speed of thought in our open, dynamic office environment. Graphite GTC stands today as a leader, not just in no-code application development, but as a full-fledged IT and consulting partner, trusted by some of the most prestigious organizations across various sectors.


Job Summary:

We are seeking a talented AI and Machine Learning Engineer to join our dynamic team in Philadelphia. In this role, you will be instrumental in developing and implementing machine learning models and algorithms that enhance our No-Code platform's capabilities. You will collaborate closely with cross-functional teams to integrate intelligent solutions that drive innovation and deliver exceptional value to our clients. The ideal candidate is passionate about machine learning, has a strong background in software development, and thrives in a fast-paced, collaborative environment. Add something about a good and scalable design


Key Responsibilities:

  • Model Development and Deployment:
  • Design, develop, and implement machine learning models and algorithms to solve complex problems and improve platform and web application functionalities.
  • Build end-to-end machine learning pipelines, from data ingestion and preprocessing to model training and deployment.
  • Develop custom algorithms for predictive modeling, classification, clustering, and anomaly detection.
  • Data Collection and Preparation:
  • Gather and analyze large, complex datasets from various sources to build robust models.
  • Perform data cleaning, feature engineering, and transformation to prepare data for modeling.
  • Ensure data quality and integrity throughout the machine learning lifecycle.
  • Algorithm Optimization and Performance Tuning:
  • Optimize models for accuracy, efficiency, and scalability using techniques such as hyperparameter tuning, regularization, and cross-validation.
  • Evaluate model performance using appropriate metrics and refine models to meet desired outcomes.
  • Implement techniques to handle imbalanced data, overfitting, and underfitting.
  • Integration and Deployment:
  • Collaborate with software engineers to integrate machine learning models into the production environment.
  • Develop APIs and services to expose machine learning functionalities within the platform.
  • Monitor models in production, implement A/B testing, and manage model versions.
  • Research and Innovation:
  • Stay current with the latest advancements in machine learning, deep learning, and artificial intelligence.
  • Experiment with new algorithms, tools, and frameworks to improve existing solutions.
  • Contribute to the company's intellectual property through innovative solutions and patents.
  • Collaboration and Cross-Functional Support:
  • Work closely with data scientists, product managers, and UX designers to understand requirements and deliver solutions.
  • Participate in code reviews, design discussions, and share best practices within the team.
  • Communicate complex technical concepts to non-technical stakeholders effectively.
  • Documentation and Compliance:
  • Maintain comprehensive documentation of models, algorithms, and processes for transparency and knowledge sharing.
  • Ensure compliance with data privacy laws, ethical guidelines, and company policies in all machine learning initiatives.
  • Develop and enforce standards for data security, model governance, and ethical AI practices.
  • Performance Monitoring and Continuous Improvement:
  • Implement monitoring tools to track model performance and detect issues in real-time.
  • Analyze feedback and performance data to identify areas for improvement.
  • Update and retrain models as needed to maintain accuracy and relevance.


Required Skills and Experience:

  • Citizenship:
  • Must be a U.S. citizen.
  • Education:
  • Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
  • Experience:
  • Minimum of 4 years of experience in machine learning engineering or a similar role.
  • Proven experience in developing, deploying, and monitoring machine learning models in production environments.
  • Technical Skills:
  • Strong proficiency in programming languages such as Python (preferred), C# Java, or C++.
  • Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Keras).
  • Familiarity with deep learning architectures (CNNs, RNNs, LSTMs, Transformers) and natural language processing (NLP) techniques.
  • Knowledge of data processing tools and databases (e.g., SQL, NoSQL, Hadoop, Spark).
  • Experience with cloud platforms (e.g., AWS SageMaker, Azure ML, Google Cloud ML) and containerization technologies (e.g., Docker, Kubernetes).
  • Proficient in using version control systems like Azure DevOps and collaborative tools like JIRA or Confluence.

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