About the Role

This role requires high-level autonomy, where you will define your own direction within strategic goals, influence multiple teams, and navigate high complexity and ambiguity to deliver tangible business results. You will bridge the gap between technical innovation and real-world business challenges by applying advanced statistical and machine learning techniques to build predictive models and derive actionable insights.

What we are looking for

• Experience & Education: Bachelor's degree in Computer Science or Engineering with 8–12 years of relevant experience leading complex technical projects with multi-team impact.
• Advanced ML & Statistics: Expert capability in designing end-to-end ML systems for complex problems (including imbalanced data and concept drift), applying advanced statistical methods (mixed models, survival analysis, Bayesian approaches), and demonstrating a deep understanding of causal inference techniques, experimentation design (A/B testing, MABs), and deep learning architectures for unstructured data (e.g., NLP, Computer Vision).
• Core Technology Stack: Expertise in Python (including libraries like Pandas and NumPy) or R, proficiency with cloud platforms and their data/ML services (e.g., AWS Sagemaker, GCP Vertex AI, Azure ML Services), experience with big data technologies (e.g., Spark, Hadoop), and familiarity with MLOps tools (e.g., Kubeflow, MLflow, Docker).
• Business Immersion: Proven ability to immerse in operations to acquire deep domain expertise, thinking like an insider to translate seamlessly between business needs and engineering solutions.
• Full-Stack Agility: Ability to build complete applications rapidly across any technology stack, selecting the right tools to balance technical debt with delivery speed.
• Data Strategy & Integration: Experience architecting scalable data strategies across diverse teams and complex enterprise landscapes. This includes defining data governance policies, mastering data quality frameworks, building robust integration solutions for undocumented schemas and disparate systems, and driving the adoption of modern data warehousing and lakehouse architectures.
• AI Evaluation & Governance: Experience leading AI governance initiatives, creating evaluation standards, and training teams on rigorous AI verification and risk management.
• Rapid Prototyping: Proficiency in leading rapid delivery initiatives using a prototype-first approach to validate solutions quickly before scaling.
• Problem Discovery: A track record of seeking out undefined problems, embedding with users to discover latent needs, and turning ambiguity into clear problem statements.
  
  

Who you are

• Polymath Oriented: You bridge gaps between engineering, design, business, and science, rapidly immersing yourself in new domains to speak the language of the business.
• Curious Explorer: You seek out ambiguity rather than avoiding it, driving team curiosity through challenging questions and creating an environment that encourages experimentation.
• Outcome Owner: You drive an accountability culture focused on business impact rather than just deliverables, owning relationships and making trade-offs between custom solutions and generalizable work.
• Systems Thinker: You map complex system interactions across technical and business domains, anticipating cascading effects and understanding how technology changes impact operations.
• Precise Communicator: You translate seamlessly between technical and business language, ensuring requirements are clear enough to enable AI generation and facilitate productive discussions with stakeholders.
• Problem Discoverer: You embed with users to discover latent needs, turning ambiguity into clear problem statements rather than waiting for defined tasks.

What Appnovation Offers 

• Challenging and rewarding work with real impact
• Direct Access to Cutting-Edge AI Platforms
• Diverse and Inclusive Culture 
• Growth opportunities for personal and professional development
• A collaborative and innovative work environment where your ideas are valued
• Exposure to exciting projects and high-profile clients
• Supportive work environment with access to company leaders
• Hybrid working model

Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry’s digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity.

Xometry is looking for a Machine Learning Engineer II who is excited about advancing machine learning capabilities and bringing models into production at scale. In this role, you’ll design, deploy, and maintain robust statistical and machine learning models, working closely with data scientists to translate research and experimentation into reliable, high-impact systems. You’ll apply strong data intuition and engineering judgment to improve model performance, reliability, and observability, while building predictive models that support pricing, cost estimation, and sourcing recommendations.

What You'll Do:

• Design, build, and optimize machine learning models to enhance Xometry’s platform and business operations.
• Analyze large datasets to extract meaningful patterns and insights.
• Collaborate with cross-functional teams to integrate machine learning models into production systems.
• Learn and apply best practices in model evaluation, performance tuning, and deployment.
• Influence technical direction by identifying opportunities to improve modeling approaches, data quality, and system architecture.
• Work across teams to ensure machine learning solutions are explainable, maintainable, and aligned with business goals.
• Help bridge the gap between research and production, ensuring models perform just as well in the real world as they do in notebooks.
• Gain exposure to cutting-edge machine learning frameworks, tools, and techniques used in the manufacturing industry.

Qualifications:

• A bachelor’s degree is required, but an advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is highly preferred.
• Experience deploying and maintaining machine learning models in production environments.
• 4+ years of experience in machine learning, focusing on data engineering and/or data science.
• Proficient in Python, including key libraries such as PyTorch, TensorFlow, pandas, and numpy.
• Strong background in probability, statistics, and optimization techniques relevant to generative modeling.
• Familiarity with cloud computing resources and tools for model training and deployment (e.g., AWS SageMaker).
• Familiar with software engineering principles, including version control, reproducibility, and continuous integration.
• Experience in the manufacturing, supply chain, or similar industries is a plus.

#LI-Remote

Xometry is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.

For US based roles: Xometry participates in E-Verify and after a job offer is accepted, will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.

Xometry is seeking a Senior Data Scientist to join our Data Science team. This person will drive data science initiatives, provide technical guidance when needed, and leverage data to solve complex business challenges. The ideal candidate has a deep understanding of data science methodologies, strong statistical expertise, and proven experience delivering impactful data solutions in a dynamic environment. This is a 1-year contract with the potential for extension.

Responsibilities:

• Use data analysis, visualization, and modeling tools (e.g., Looker, Jupyter Notebooks, Python, Pandas) to drive data-driven business strategies, with a focus on cost prediction for a two-sided marketplace.
• Design and execute data science projects, including hypothesis development, statistical analysis, and experimentation (e.g., A/B testing) to answer key business questions and validate assumptions.
• Collaborate with cross-functional teams to translate business needs into data science solutions and ensure alignment with Xometry’s objectives.
• Analyze existing algorithms for accuracy and performance, provide recommendations for optimization, and update production code as necessary.
• Query and extract data from databases (e.g., Snowflake, MongoDB) to support analysis and model development.
• Implement robust data science methodologies, emphasizing best practices in code reproducibility, version control, and model deployment.
• Continuously iterate and improve solutions within a fast-paced, agile environment, addressing challenges with innovative, data-driven approaches.
• Foster a culture of collaboration, teamwork, and continuous learning, encouraging knowledge sharing and skill development within the team.

Qualifications:

• A bachelor’s degree is required; an advanced degree (M.S. or PhD) in applied math, computer science, data science, engineering, or a related field is highly preferred.
• 5+ years of experience in data science
• Strong expertise in SQL and Python (numpy, scipy, pandas, and scikit-learn preferred) and experience with API integrations using Python.
• Proficient in applied statistics, including knowledge of probability distributions, confidence intervals, statistical tests (e.g., t-tests, ANOVA, Chi-Square), and power analysis.
• Experience with pricing algorithms and technology-driven product development.
• Knowledge of scientific software principles, including version control, code reproducibility, and deployment practices.
• Demonstrated ability to work in a fast-paced, ambiguous environment and manage shifting priorities effectively.
• Must be able to work core hours aligned with US Eastern Time (GMT-5).
• Strong communication and interpersonal skills to collaborate with global teams and articulate complex technical information to non-technical stakeholders.

#LI-Remote

Xometry is seeking a Senior Data Scientist to join our Generative AI team. The candidate will focus on training and fine-tuning Visual Language Models (VLMs) for multimodal document understanding. The ideal candidate will leverage their expertise in machine learning and computer vision to advance Xometry's capabilities in processing and extracting structured data from complex documents and images. This is a 1-year contract.  

Responsibilities:

• Develop, fine-tune, and evaluate Visual Language Models (VLMs) to enhance document understanding, focusing on multimodal data such as text, images, and technical drawings.
• Design and implement data preparation, cleaning, and augmentation processes tailored to multimodal model training, ensuring high-quality data pipelines for VLMs.
• Leverage transfer learning and pre-trained models to accelerate model development and optimize performance on Xometry’s specific data.
• Use cloud resources (e.g., Amazon Web Services) to scale training and fine-tuning processes for VLMs efficiently.
• Collaborate with data engineering and machine learning operations (MLOps) teams to deploy VLMs into production and monitor their performance.
• Interpret model outputs and improve model accuracy and robustness by applying data analysis and visualization tools (such as Python, Jupyter Notebooks, and SQL).
• Experiment with and implement state-of-the-art model architectures, continuously optimizing VLM performance in a fast-paced, iterative environment.
• Work within a team-oriented setting, participating in peer reviews, sharing insights, and contributing to an environment of continuous learning and improvement.

Qualifications:

• A bachelor’s degree is required; an advanced degree (M.S. or PhD) in computer science, data science, machine learning, or a related field is highly preferred.
• 5+ years of experience in data science and machine learning, with expertise in Visual Language Models or multimodal machine learning.
• Strong experience with machine learning libraries and frameworks such as PyTorch, TensorFlow, or Hugging Face.
• Proficiency in Python, including libraries like pandas, numpy, and scikit-learn.
• Solid understanding of deep learning techniques and experience with transfer learning, fine-tuning, and model evaluation.
• Experience with cloud platforms (e.g., AWS SageMaker) for model training and deployment.
• Familiarity with data processing and visualization tools (SQL, Jupyter Notebooks, Looker, etc.) and basic database knowledge (e.g., Snowflake, MongoDB).
• Excellent analytical and problem-solving skills, with a strong ability to work in an environment that values teamwork, innovation, and continuous learning.
• Familiarity with computer vision tasks and frameworks, as well as experience with multimodal data, is a plus.

#LI-Remote