Principal Machine Learning Engineer Job at Zalando (Berlin)

Principal Machine Learning Engineer

VideoAmp is on a mission to create the best employee and workplace experience wh...

Location

United States , Los Angeles; New York; Boulder; Chicago; Dallas; St. Petersburg

Salary:

184000.00 - 200000.00 USD / Year

VideoAmp

Expiration Date

Until further notice

Requirements

7+ years of experience in Machine Learning Engineering, Data Engineering, or a similar technical role
Expert-level proficiency in Python, ML frameworks, Temporal, and distributed data processing (Spark, Hive)
Experience with making models reproduceable as needed
Deep understanding of data quality methodologies, fault-tolerant data systems, and validation frameworks
Strong experience designing and scaling ML infrastructure, automated pipelines, and production-grade deployment workflows
Hands-on experience with cloud-native architectures, ideally on AWS
Expertise with CI/CD, version control, and modern DevOps practices
Strong communicator with the ability to translate complex technical concepts into clear, actionable insights
Demonstrated ability to lead cross-functional technical initiatives with minimal guidance

Job Responsibility

Architect and lead development of advanced machine learning models, quality frameworks, and large-scale data validation systems that power VideoAmp’s measurement and optimization products
Design and optimize ML infrastructure, including scalable distributed pipelines, model lifecycle tooling, and automated validation frameworks
Lead experimentation strategies, including model benchmarking, reproducibility, evaluation methodologies, and statistical validation
Drive data quality standards across the organization by partnering with Data Engineering, Core Engineering, and Measurement Science teams
Own cross-functional initiatives end-to-end, from requirements definition through production deployment, monitoring, and iteration
Influence technical direction, contributing to architectural decisions, design reviews, and long-term platform strategy
Mentor and uplevel engineers, providing guidance on ML best practices, system design, data quality, and code excellence
Communicate complex findings, insights, and recommendations to technical and non-technical stakeholders

What we offer

Discretionary and flexible paid time off
In addition to standard US holidays off, VideoAmp employees also partake in Spring, Summer and Winter breaks
Comprehensive medical, dental, and vision benefits for you and your dependents—including multiple options fully covered by VideoAmp
Unlimited financial wellness sessions with Origin financial advisors
401k Plan with matching
HSA & FSA
Commuter Benefits
Cell Phone Reimbursement
Paid Maternity and Parental Leave for All Family Additions
Equity

Fulltime

Principal Machine Learning Engineer

As a Principal Machine Learning Engineer in ZMS, you will be the tech lead worki...

Location

Germany , Berlin

Salary:

Not provided

Zalando Sverige

Expiration Date

Until further notice

Requirements

Excellent software development engineering skills to design computationally effective solutions for machine learning operationalization and maintenance (MLOps/MLaaS) in large-scale production environments (data engineering, data version control, model serving, continuous monitoring & alerting)
Strong verbal and written communication and presentation abilities when discussing complex ideas with both technical and non-technical stakeholders alike
Hands-on professional experience in programming, using Python, Java Flink, pySpark, PyTorch, and TensorFlow
Strong programming skills with a high performance language (Java, Scala, Go, etc) and experience working with Python in production
Experience building, deploying and operating data-driven systems in a cloud environment, including experience with feature stores & feature engineering pipelines, data ingestion & transformation, machine learning workflow orchestration
Thrive to coach and mentor senior engineers, and work closely with applied scientists, senior machine learning engineers and data scientists

Job Responsibility

Drive the operationalization of solutions deployed in production, and help the team grow and cultivate best practices in software development and MLOps
Architect and lead the development of machine learning solutions that can handle low latency, high availability and high volume scenarios
Mentor engineers and provide technical guidance across multiple projects simultaneously while managing competing priorities effectively within agreed-upon timelines
Apply techniques and create processes to optimise deployed models for better performance, latency, and memory usage
Work closely with applied science and engineering teams, product managers and other business stakeholders to bring our state-of-the-art solutions to customers and to discover and identify new opportunities

What we offer

27 days of holiday a year to start for full-time employees (+1 day for every calendar year up to 30 days)
2 paid volunteering days a year
Hybrid working model with up to 60% remote per week
Work from abroad for up to 30 working days a year
Employee shares program
40% off fashion and beauty products sold and shipped by Zalando, 30% off Lounge by Zalando, discounts from external partners
Relocation assistance available (subject to prior agreement)
Family services, including counseling and support
Health and wellbeing options (including Wellhub, formerly Gympass)
Mental health support and coaching available

Fulltime

Principal Machine Learning Engineer

As a Principal Machine Learning Engineer, you will lead the architecture and dev...

Location

India , Hyderabad

Salary:

Not provided

Amgen

Expiration Date

Until further notice

Requirements

Bachelor’s degree in computer science, Engineering, Data Science, or a related field with 12 to 17 years of total experience
8+ years of experience in software engineering, machine learning engineering, or ML infrastructure
Strong experience building production ML systems or ML platforms
Hands-on experience with MLOps frameworks and tools such as MLflow / Equivalent - Model lifecycle management frameworks
Strong programming experience in Python and modern software engineering practices such as API Driven Architecture and Event based systems
Experience designing scalable distributed systems or cloud-native architectures
Experience deploying and operating machine learning models in production environments
Solid understanding of modern ML workflows including training, evaluation, deployment, monitoring, and retraining

Job Responsibility

Architect and build a scalable ML platform for training, deployment, and lifecycle management of ML, LLM, and Generative AI models
Lead development of infrastructure that supports production hosting of complex AI systems, including large-scale inference workloads
Design developer-friendly abstractions and automation that make it easy for researchers to build and deploy models within the Amgen ecosystem
Implement and evolve MLOps capabilities including experiment tracking, model versioning, CI/CD for ML, monitoring, and reproducibility using tools such as Databricks and MLflow
Build platform capabilities supporting Generative AI and emerging Agentic AI systems
Serve as the technical leader for a team of engineers, guiding architecture, design reviews, and engineering best practices
Partner with AI researchers, data scientists, and platform teams to translate cutting-edge AI research into reliable production systems
Evaluate and adopt emerging technologies across the modern AI stack including foundation models, vector databases, agent frameworks, and model serving systems
Champion AI-native engineering practices, leveraging tools like GitHub Copilot, Codex, and AI-assisted development workflows
Contribute to the broader strategy and evolution of the Enterprise AI Platforms ecosystem

Principal Machine Learning Engineer

This is a high-leverage leadership role that spans architecture, execution, and ...

Location

India , Bengaluru

Salary:

Not provided

Ema

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s (or PhD) degree in Computer Science, Machine Learning, Statistics, or a related field
A strong track record (usually 10-12+ years) of applied experience with ML techniques, especially in large-scale settings
Experience building production ML systems that operate at scale (latency / throughput / cost constraints)
Experience in Knowledge retrieval and Search space
Exposure in building Agentic Systems and Frameworks
Proficiency in relevant programming languages (e.g. Python, C++, Java) and ML frameworks (TensorFlow, PyTorch, etc.)
Strong understanding of the full ML lifecycle: data pipelines, feature engineering, model training, serving, monitoring, maintenance
Experience designing systems for monitoring, diagnostics, logging, model versioning, etc.
Deep knowledge of computational trade-offs: distributed training, inference, optimizations (e.g. quantization, pruning, batching)
Excellent communication skills

Job Responsibility

Lead the technical direction of GenAI and agentic ML systems that power enterprise-grade AI agents — spanning reasoning, retrieval, tool use, and integrations across various SaaS products
Architect, design, and implement scalable production pipelines for model training, fine-tuning, retrieval (RAG), agent orchestration, and evaluation — ensuring robustness, latency efficiency, and continuous learning
Define and own the multi-year ML roadmap for GenAI infrastructure — including agent frameworks, RAG systems, world-class evaluation loops, and integration with MCP, browser, and vision pipelines
Identify and integrate cutting-edge ML methods / research (deep learning, large models, recommender systems, LLMs, etc.) into Ema’s products or infrastructure
Research, prototype, and integrate cutting-edge ML and LLM advancements (reasoning, memory architectures, multi-modal perception, long-context models, autonomous agents) into the platform
Optimize trade-offs between accuracy, latency, cost, interpretability, and real-world reliability across the agent lifecycle — from prompt design to orchestration and execution
Champion engineering excellence — drive observability, reproducibility, versioning, testing, and bias-aware development across ML and agentic systems
Mentor and elevate senior engineers and researchers, fostering a culture of scientific rigor, experimentation, and system-level thinking
Collaborate cross-functionally with product, infra, and research teams to align ML innovation with enterprise needs — enabling secure integrations, privacy-aware deployments, and scalable use cases
Influence data strategy — guide how retrieval indices, embeddings, structured/unstructured corpora, and feedback loops evolve to improve grounding, factuality, and reasoning depth

Fulltime

Principal Machine Learning Engineer

With Prisma AIRS, Palo Alto Networks is building the world's most comprehensive ...

Location

United States , Santa Clara

Salary:

185200.00 - 299475.00 USD / Year

Palo Alto Networks

Expiration Date

Until further notice

Requirements

BS/MS or Ph.D. in Computer Science, a related technical field, or equivalent practical experience
Extensive professional experience in software engineering with a deep focus on MLOps, ML systems, or productionizing machine learning models at scale
Expert-level programming skills in Python are required
Deep, hands-on experience designing and building large-scale distributed systems on a major cloud platform (GCP, AWS, Azure, or OCI)
Proven track record of leading the architecture of complex ML systems and MLOps pipelines using technologies like Kubernetes and Docker
Mastery of ML frameworks (TensorFlow, PyTorch) and extensive experience with advanced inference optimization tools (ONNX, TensorRT)
A strong understanding of popular model architectures (e.g., Transformers, CNNs, GNNs) is a must
Demonstrated expertise with modern LLM inference engines (e.g., vLLM, SGLang, TensorRT-LLM) is required

Job Responsibility

Lead the architectural design of a highly scalable, low-latency, and resilient ML inference platform capable of serving a diverse range of models for real-time security applications
Define technical approaches to less-defined product requirements, ensuring the best fit between product features and technical implementation
Explore new product opportunities by maintaining a deep understanding of LLM and Generative AI research trends
Provide technical leadership and mentorship to the team, driving best practices in MLOps, software engineering, and system design
Drive the strategy for model and system performance, guiding research and implementation of advanced optimization techniques like custom kernels, hardware acceleration, and novel serving frameworks
Establish and enforce engineering standards for automated model deployment, robust monitoring, and operational excellence for all production ML systems
Act as a key technical liaison to other principal engineers, architects, and product leaders to shape the future of the Prisma AIRS platform and ensure end-to-end system cohesion
Tackle the most ambiguous and challenging technical problems in large-scale inference, from mitigating novel security threats to achieving unprecedented performance goals

What we offer

restricted stock units
bonus
employee benefits

Fulltime

Principal Machine Learning Engineer

Lime is hiring a Principal Machine Learning Engineer to join the Data Science & ...

Location

Canada

Salary:

192000.00 - 264000.00 CAD / Year

Lime

Expiration Date

Until further notice

Requirements

8+ years of professional experience in software engineering or applied ML, with a record of delivering production level systems
Fluency in Python
Experience with modern ML frameworks (e.g., PyTorch, TensorFlow) and data tools (e.g. SQL, pandas, spark, airflow)
Strong foundation in ML fundamentals, including model evaluation, experimentation, optimization, production deployment, and operations
Strong system design skills and comfort working with distributed systems
Track record of influencing ML architecture and practices across multiple teams

Job Responsibility

Drive alignment across teams on ML strategy, standards, and long-term technical direction by serving as a technical leader for Lime’s ML Center of Excellence
Guide recommendations for ML infrastructure, tooling, and architecture (training, serving, feature stores, experimentation, monitoring)
Define and evolve ML development processes, including model review, experimentation rigor, deployment, optimization, and operations
Establish best practices for ML monitoring, observability, alerting, and model performance health in production
Drive reusable feature development patterns and shared ML capabilities that enable teams to move faster and more safely
Partner with platform, data, and product engineering teams to ensure ML systems are reliable, scalable, and cost effective
Identify and prioritize opportunities where ML will improve Lime’s product, operations, or efficiency
Act as a force multiplier by mentoring data scientists and machine learning engineers, raising the quality bar for machine learning across Lime

What we offer

Offers Equity
Offers Bonus

Fulltime

Principal Machine Learning Engineer

Lime is hiring a Principal Machine Learning Engineer to join the Data Science & ...

Location

United States

Salary:

240000.00 - 330000.00 USD / Year

Lime

Expiration Date

Until further notice

Requirements

8+ years of professional experience in software engineering or applied ML, with a record of delivering production level systems
Fluency in Python and experience with modern ML frameworks (e.g., PyTorch, TensorFlow) and data tools (e.g. SQL, pandas, spark, airflow)
Strong foundation in ML fundamentals, including model evaluation, experimentation, optimization, production deployment, and operations
Strong system design skills and comfort working with distributed systems
Track record of influencing ML architecture and practices across multiple teams

Job Responsibility

Drive alignment across teams on ML strategy, standards, and long-term technical direction by serving as a technical leader for Lime’s ML Center of Excellence
Guide recommendations for ML infrastructure, tooling, and architecture (training, serving, feature stores, experimentation, monitoring)
Define and evolve ML development processes, including model review, experimentation rigor, deployment, optimization, and operations
Establish best practices for ML monitoring, observability, alerting, and model performance health in production
Drive reusable feature development patterns and shared ML capabilities that enable teams to move faster and more safely
Partner with platform, data, and product engineering teams to ensure ML systems are reliable, scalable, and cost effective
Identify and prioritize opportunities where ML will improve Lime’s product, operations, or efficiency
Act as a force multiplier by mentoring data scientists and machine learning engineers, raising the quality bar for machine learning across Lime

What we offer

A choice of medical, dental, and vision plans
company-paid life and disability insurance
company-funded mental health benefits
401(k) plan with both pre-tax and Roth options
access to a Health Savings Account (HSA) with a monthly company contribution
Paid parental leave for birthing and non-birthing parents
fertility and family-forming benefits
Unlimited vacation
paid leaves
10 company holidays

Fulltime

Principal Machine Learning Engineer

Health Futures is a Research and Incubation team working at the intersection of ...

Location

United States , Redmond

Salary:

139900.00 - 274800.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C++, C#, Java, JavaScript, or Python
OR equivalent experience
Masters in Computer Science or related technical field AND 6+ years technical engineering experience including significant work in machine learning or applied AI
OR equivalent experience
Proven track record of designing and deploying large-scale ML or MLops systems in research or product settings
Hands-on experience with large-scale distributed training of ML models
Deep expertise in ML algorithms, model optimization, and frameworks (e.g., PyTorch, TensorFlow)
Experience with one or more of: optimizing data mixes, mid-training, post-training, model merging, or model distillation
Familiarity with security and compliance standards for enterprise and health data
Demonstrated ability to communicate effectively and solve problems in collaborative, research-driven environment

Job Responsibility

Lead the design and development of machine learning models and systems for health and life sciences applications, ensuring scalability and reliability
Define technical strategy and architecture for ML pipelines, including data ingestion, feature engineering, model training, evaluation, and deployment
Collaborate with interdisciplinary teams (including scientists, researchers, and software engineers) to envision and develop AI-augmented scientific systems
Mentor engineers and researchers, promoting best practices in ML development, experimentation, and responsible AI principles
Ensure security, privacy, and regulatory compliance across ML workflows and data handling

Fulltime

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Principal Machine Learning Engineer

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Principal Machine Learning Engineer

Principal Machine Learning Engineer

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Principal Machine Learning Engineer

Principal Machine Learning Engineer

Principal Machine Learning Engineer

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Principal Machine Learning Engineer

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