Staff AI/ML Research & Development Engineer, Welocalize
2+ days a week in office
Translation & localization for global businesses
Be an early applicant
Translation & localization for global businesses
1001+ employees
Be an early applicant
2+ days a week in office
1001+ employees
Company mission
To bridge language and AI to power global success in even the most complicated and regulated environments.
Role
Who you are
- BSc in Computer Science, Mathematics or similar field; Master’s degree is a plus
- 8+ years of experience in AI/ML Engineering or similar roles
- Advanced Programming Skills: Proficiency in programming languages like Python, R, or Java, with a strong emphasis on writing clean, efficient, and scalable code
- Expertise in Machine Learning Algorithms: Deep understanding of a wide range of machine learning techniques, including both classical algorithms and modern deep learning approaches
- Strong Statistical Analysis and Modeling: Advanced knowledge in statistics and the ability to apply these concepts to model development and data analysis
- Data Engineering Proficiency: Skills in managing and processing large datasets, including expertise in big data technologies like Hadoop, Spark, or Kafka
- Deep Learning Frameworks: Proficiency in using deep learning frameworks such as TensorFlow, PyTorch, or Keras for building complex models
- Cloud Computing and MLOps: Experience with cloud platforms like AWS, Azure, or Google Cloud, and knowledge of MLOps practices for efficient model deployment and maintenance
- Natural Language Processing and Computer Vision: Skills in specialized areas like NLP and computer vision, depending on project requirements
- Strong Problem-Solving Abilities: Advanced problem-solving skills to tackle complex challenges in machine learning projects
- Leadership and Mentorship: Ability to lead project teams and mentor junior engineers, fostering a collaborative and innovative environment
- Effective Communication: Excellent communication skills for articulating complex technical concepts to both technical and non-technical stakeholders
- Project Management: Strong project management skills, capable of overseeing multiple projects and ensuring timely and successful delivery
- Ethical AI Practices: Deep understanding of ethical AI principles, ensuring the development of fair, unbiased, and transparent machine learning models
- Continuous Learning: Commitment to continuous learning and staying abreast of the latest advancements in AI and machine learning technologies
What the job involves
- A Staff Machine Learning Engineer plays a pivotal role in leading and architecting complex machine learning projects, often acting as a bridge between technical teams and senior management
- They are responsible for designing advanced algorithms, mentoring junior engineers, and driving strategic decisions to effectively integrate AI solutions into business processes
- At Welocalize, we embrace a flexible, delivery-focused culture where success is measured by results, not rigid schedules
- Team members are trusted to manage their own time, as long as commitments and deliveries are met
- The core hours are 4pm–6 pm CET, were our global team, from the west coast of US to India, is simultaneously online
- Important cross-team meetings often take place in that time slot
- Leads Project Development: Strategically leads the development of complex machine learning projects, ensuring they align with business objectives. This involves setting timelines, defining milestones, and coordinating with various teams
- Architects ML Solutions: Expertly architects and designs advanced machine learning models and systems, considering scalability, efficiency, and integration with existing infrastructure
- Mentors Junior Engineers: Actively mentors junior machine learning engineers, providing guidance and support to foster their professional growth and enhance team capabilities
- Coordinates with Cross-Functional Teams: Regularly coordinates with cross-functional teams, including local project management teams, globally based business development teams, and other technical units, ensuring cohesive progress and alignment with broader company goals
- Drives Innovation: Continuously drives innovation by researching and implementing cutting-edge techniques and technologies in machine learning and artificial intelligence
- Manages Stakeholder Relationships: Effectively manages relationships with key stakeholders, including senior management, to communicate project progress, challenges, and outcomes
- Ensures Ethical AI Practices: Vigilantly ensures that all AI models and practices adhere to ethical guidelines, promoting responsible and unbiased AI development
- Evaluates Project Outcomes: Critically evaluates the outcomes of machine learning projects, assessing their impact on business goals and identifying areas for improvement
- Presents Technical Insights: Articulately presents technical insights and project updates to both technical and non-technical audiences, ensuring clarity and understanding
- Facilitates Knowledge Sharing: Fosters a culture of knowledge sharing and continuous learning within the team, organizing workshops, and training sessions as needed
- Success Indicators for a Staff AI/ML Engineer:
- Innovative and Effective Solutions: Success is marked by the development of innovative machine learning solutions that significantly enhance business processes and outcomes
- Strong Leadership and Mentorship: Demonstrated ability to lead projects effectively and mentor junior team members, contributing to the overall strength and expertise of the team
- Positive Stakeholder Engagement: Effective engagement with stakeholders, ensuring their needs are met and their understanding of complex ML concepts is clear
- Ethical and Responsible AI Development: Upholding the highest standards of ethical AI practices, ensuring solutions are fair, unbiased, and responsible
- Continuous Improvement and Learning: A commitment to continuous learning and improvement, both personally and within the team, keeping abreast of the latest developments in the field
Our take
According to the CSA, while only 16% of the global population speaks English as their native language, approximately 60% of the top 10M websites are in English. With over 250 language options, Welocalize enables companies to unlock business opportunities at a global scale by transforming and localizing its clients’ online websites and content.
The company has made an impressive number of strategic acquisitions over the years, widening its reach across a range of industries including digital content marketing, litigation support, and healthcare, and is a trusted multilingual solution for 2,000+ global company clients (including Disney, Uber, Dell, TNT, and Blackboard).
Founded in 1997, the company is currently the 4th largest language service provider in North America and the 9th largest provider globally. Welocalize is well-positioned to see continued growth as it furthers its market-leading presence, including by making moves to strengthen its leadership team moving forward.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
28% employee growth in 12 months
Company
Funding (1 round)
Nov 2010
$34m
GROWTH EQUITY VC
Total funding: $34m
Company HQ
Midtown South, New York, NY
Leadership
Paul Carr
(CEO)Prior to joining Welocalize in 2023, Paul was a President at Third Bridge Group for 4 years and a President at Axiom for 10 years. He also spent 4 years at American Express as a VP and Head of Strategy/GM of International Insurance Services.
Chris Grebisz
(CTO)Chris joined Welocalize in 2002, leaving the team in 2008 to work in leadership roles at various Software Development companies. He then returned to Welocalize in 2013 and has since led operations in the Americas and now oversees the companies digital transformation and technology development worldwide.
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