Work with large-scale multimodal datasets (text, unstructured and structured data), developing advanced preprocessing, augmentation, and content understanding techniques
Architect and guide the implementation of scalable data pipelines and architectures
Perform in-depth requirements analysis, collaborating with team members at different levels and documenting solutions
Contribute to technical execution by writing well-structured, high-performance code for production ML pipelines
Set the technical direction by identifying key challenges and defining innovative solutions
Mentor and guide junior engineers, fostering a culture of technical excellence and knowledge-sharing within the team
Architect, develop, and optimize production-level ML solutions, focusing on scalability and reliability, while contributing to engineering best practices
Establish best practices for model experimentation, evaluation, and optimization
Communicate technical findings effectively, influencing stakeholders through quantitative analysis, qualitative insights, and clear visual presentations
Requirements
pytorch
spark
aws
llms
ms
deep learning
Proven ability to translate theoretical concepts into practical solutions and prototype implementations
Expertise in deep learning architectures (e.g., Transformers, CNNs, GANs) and modern ML frameworks (e.g., PyTorch, Lightning, Ray)
Proficiency in parallel and distributed computing techniques, with hands-on experience using platforms like Spark, Ray, or similar distributed systems for large-scale data processing and model training
You seek innovative solutions to difficult technical problems and iterate quickly on ideas
Excellent technical writing and communication skills for documentation, presentations, and influencing cross-functional teams
An MS in Machine Learning, Artificial Intelligence, Mathematics, Statistics, Computer Science, or a related field
Experience with LLMs and related technologies, including frameworks, embedding models, vector databases, and Retrieval-Augmented Generation (RAG) systems, in production settings
You are comfortable driving progress in newly forming, ambiguous areas where learning and adaptability are key
Experience with AWS cloud services and SageMaker Studio for scalable data processing and model development
You easily collaborate with others and are comfortable with minimal direction
Background in Architecture, Engineering, or Construction
7-10+ years of experience in machine learning engineering or a related field, with a proven track record of leadership and hands-on implementation
Proven record in developing and deploying high-scale machine learning algorithms in production environments
Deep understanding of data modeling, system architectures, and processing techniques.
Extensive experience in data preparation, hyper-parameter selection; acceleration techniques; and optimization methods
Strong foundation in computer science fundamentals, distributed computing, and algorithmic efficiency
Ability to work autonomously while effectively collaborating across teams, bridging the gap between research and practical implementation
Benefits
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Training + Development
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Interview process
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Visa Sponsorship
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Security clearance
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Company
Overview
Founded in 1982
Year of establishment
Marks the beginning of Autodesk's journey in pioneering design software solutions.
Pioneered software for 2D and 3D design, revolutionizing industries.
Known for products like AutoCAD, it reshaped architecture, engineering, and manufacturing workflows.
Empowering creators in fields from construction to digital media, enabling more innovative designs.
Develops tools used in iconic projects, from skyscrapers to blockbuster movies.
Pushes the boundaries of design technology, leading the way in artificial intelligence and automation.
Software is a cornerstone in diverse sectors, from industrial to infrastructure, energy, and entertainment.
Cloud-based solutions streamline design processes and foster real-time collaboration across industries.
A leader in 3D design software, with solutions powering projects in every corner of the globe.
Committed to shaping the future of digital design, bringing complex visions to life.
Culture + Values
Innovation: We believe in the power of creativity to push boundaries and change the world.
Collaboration: We work together to create solutions that make a difference.
Customer Success: We are focused on delivering products and services that help our customers succeed.
Sustainability: We are committed to making a positive impact on the planet and communities.
Integrity: We act with honesty and uphold the highest ethical standards.
Inclusion: We embrace diverse perspectives and strive for an environment where everyone belongs.
Environment + Sustainability
2023
Net-zero commitment
Aiming to achieve net-zero carbon status, a critical step in combating climate change.
35%
Carbon emissions reduction
Significant reduction in overall carbon footprint across all emission scopes since 2019.
Designing products that help users make more sustainable decisions, including tools for low-carbon building design.
Aims to advance climate resilience by providing tools to better predict and plan for climate risks.
Promotes circular design principles and helps customers optimize material use and reduce waste.
Inclusion & Diversity
30% Female Workforce
Gender Diversity
As of 2023, 30% of the global workforce identifies as female, highlighting progress in gender diversity across the organization.
25% Leadership Representation
Female Leadership
25% of leadership positions are held by women, indicating strides toward gender parity in executive roles.
2025 Diversity Goal
Leadership Commitment
A strategic initiative to boost representation of underrepresented groups in leadership positions by 2025.
12 Employee Groups
Employee Resource Networks
Twelve employee resource groups are supported, fostering inclusion and community for diverse populations including women, LGBTQ+, and veterans.
Leadership Commitment: Has set a goal to increase representation of underrepresented groups in leadership by 2025.
Inclusive Hiring: Implements inclusive recruitment practices and strives for diverse candidate slates for all roles.