Learning Process Engineer Job at PassiveLogic (Amsterdam)

Learning Process Engineer

This is a career-defining opportunity to play a crucial role in a hyper-scale AI...

Location

United States , Salt Lake City

Salary:

Not provided

PassiveLogic

Expiration Date

Until further notice

Requirements

Technical background in computer science, AI/ML, data engineering, or knowledge systems
Experienced with graph databases (Neo4j, TigerGraph, Weaviate, Neptune), Python/C++, graph query languages (Cypher, Gremlin, GraphQL, SPARQL), graph ML/embeddings, and building ETL pipelines, event-driven systems, and real-time feedback loops
Understanding of feedback-driven model improvement, reinforcement learning, or adaptive systems
Experience working cross-functionally with engineers, designers, and product managers
Analytical mindset: ability to define success metrics, run experiments, and interpret results
Excellent communication skills and a collaborative, problem-solving approach
Background in process engineering, systems design, product operations, or applied AI/ML
Strong systems thinking: ability to model complex workflows and simplify them into actionable processes
Familiarity with human-in-the-loop learning, adaptive systems, or feedback-driven workflows
Proven experience: 5+ years in developing software with an ecosystem nature

Job Responsibility

Architect feedback pipelines: Build and maintain data ingestion and labeling processes that transform user interactions into structured learning signals
Design graph-based knowledge structures: Model, update, and optimize workflows in a graph database (e.g., Neo4j, ArangoDB, Weaviate, or similar)
Implement adaptive logic: Use graph queries and embeddings to inform recommendations, predictions, and workflow adaptation
Integrate human-in-the-loop learning: Deploy mechanisms that incorporate user corrections and contextual feedback into graph representations and model updates
Collaborate with ML and software engineers: Define retraining strategies, model evaluation criteria, and experiment frameworks that leverage graph-based data
Automate performance monitoring: Develop dashboards and metrics for tracking how graph-driven learning impacts system accuracy, adoption, and efficiency

What we offer

Competitive compensation
Generous equity share package
Medical, dental and vision coverage
Disability and life Insurance options
Flex PTO
Team-building events
Free catered lunch in the office Monday — Friday
Free ski pass (We are at the base of Big Cottonwood Canyon)
Free National Park pass
Onsite Gym

Fulltime

Staff Engineer (Process Engineer)

A Staff Engineer is responsible for equipment Re-design, implementing, controlli...

Location

United States , Jefferson

Salary:

84000.00 - 108000.00 USD / Year

Nestlé Purina

Expiration Date

Until further notice

Requirements

Bachelor’s degree in engineering or a related field
3+ years of experience in an engineering role within a manufacturing, industrial, military or related environment

Job Responsibility

Analyze loss data to identify and prioritize projects to be executed in factory's continuous improvement plan
Run capital projects through the engineering team including project management, quoting, and contractor management
Initiate and lead process/equipment improvements that will increase throughput, reduce scrap, improve quality, and eliminate losses
Drive and mobilize resources to conduct problem solving on systems or equipment through failure modes & effects analysis (FMEA) and other Six Sigma methodology
Understand Nestle Continuous Excellence program and the respective TPM Pillars and tools
Participate in design, commissioning, and startup of new equipment/processes, collaborate/Align with OSL, NPE
Routine of sharing/benchmarking redesign (includes feedback to design – Capital Installation) activities for respective location
Market led routine
Creating and improving standards that enable sustainability of high preforming production processes
Supporting training programs that develop high performing operators and technicians

What we offer

401k with company match
healthcare coverage
broad range of other benefits
performance-based incentives

Fulltime

New

Senior Machine Learning Engineer, AI Platform

The AI Platform team is responsible for building the foundational infrastructure...

Location

United States; Canada

Salary:

139000.00 - 218000.00 USD / Year

Mozilla

Expiration Date

Until further notice

Requirements

Bachelor’s degree with 4–6 years of relevant industry experience, or Master’s degree with significant hands-on experience building and operating production ML systems, or work experience equivalent
Strong experience developing in Python for machine learning systems, backend services, or distributed data processing
Proven experience deploying and operating ML workloads in cloud environments, including production-grade infrastructure
Solid understanding of model serving architectures, inference pipelines, and performance tradeoffs (latency, throughput, cost, scaling strategies)
Hands-on experience working with GPU-based workloads and accelerated computing in production settings
Experience designing CI/CD pipelines and development workflows that support reliable ML system deployment
Ability to independently scope and drive technical initiatives while balancing product and operational priorities
Strong problem-solving skills and the ability to debug performance and reliability issues in distributed systems
Clear and effective communication skills, with experience collaborating across engineering, product, and infrastructure teams

Job Responsibility

Design, build, and operate core AI platform components used to train, deploy, and serve machine learning models in production environments
Own model serving and inference workflows end-to-end, driving improvements in reliability, scalability, performance, and operational excellence
Lead efforts to optimize inference systems for throughput, latency, and cost efficiency across CPU and GPU workloads
Design and manage GPU-based inference and training workloads, including performance tuning, capacity planning, and resource utilization optimization
Own and improve critical parts of the model lifecycle, including packaging, versioning, testing strategies, validation, and deployment automation
Implement and evolve observability practices (metrics, logging, tracing, alerting) to improve visibility and operational resilience of ML services and pipelines
Partner closely with product, infrastructure, security, and data teams to design scalable platform capabilities that enable AI-powered features
Contribute to technical design discussions, propose architectural improvements, and mentor junior engineers through code reviews and knowledge sharing
Participate in and help improve operational processes, including incident response, on-call rotations, and post-incident reviews

What we offer

Generous performance-based bonus plans
Rich medical, dental, and vision coverage
Generous retirement contributions with 100% immediate vesting
Quarterly all-company wellness days
Country specific holidays plus a day off for your birthday
One-time home office stipend
Annual professional development budget
Quarterly well-being stipend
Considerable paid parental leave
Employee referral bonus program

Fulltime

New

Senior Machine Learning Engineer – AV Labs

Uber is launching AV Labs to accelerate the autonomous technology ecosystem. We'...

Location

United States , Sunnyvale

Salary:

202000.00 - 224000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

4+ years of working experience in the ML/Robotics industry
Bachelor's degree in Computer Science, Computer Engineering, or related fields
Proficient in Python and Linux environments
Familiar with modern AI/ML frameworks (e.g., PyTorch).

Job Responsibility

Algorithm Development: Lead the development of autonomy algorithms and foundation models that extract high-fidelity semantic meaning from complex urban edge cases to enrich our L4 data lake
Systems Architecture Design: Architect scalable ML systems, including management of upstream sensor dependencies
Technical Leadership: Partner with fellow engineers to architect, design, and build scalable solutions for ML technology that can stand the test of scale and availability
Dataset Optimization: Deliver high-quality datasets to accelerate ML technologies through advanced sensor data collection, processing, and auto-labeling
Cross-Functional Collaboration: Partner with platform, product, and security engineering teams to enable the successful deployment of the latest machine learning techniques into production.

What we offer

Bonus program
Equity award & other types of comp
401(k) plan
Various benefits

Fulltime

New

Staff Artificial Intelligence Machine Learning Engineer

The Role: General Motors is seeking a Staff AI/ML Engineer for the Vehicle Mech...

Location

United States , Austin

Salary:

Not provided

General Motors

Expiration Date

Until further notice

Requirements

Graduate degree (Master's or PhD) in Computer Science, Data Science, Machine Learning, Statistics, Engineering, or a closely related quantitative field
7+ years of hands-on experience designing, building, and operating machine learning systems in production environments
Strong proficiency in Python (production-quality code, testing, packaging) and SQL, with experience working in shared, multi-developer codebases
Practical experience with core ML frameworks such as PyTorch, TensorFlow, or scikit-learn, and with MLOps tooling (e.g., MLflow, CI/CD, model registries, experiment tracking)
Experience building data and ML workloads on cloud platforms, preferably Microsoft Azure, and working with Databricks, Spark, or similar distributed processing frameworks
Demonstrated ability to turn ambiguous real-world problems into shippable AI/ML solutions, owning the details from data exploration through deployed service and ongoing operation
Strong understanding of ML system behavior in production (data issues, non-stationarity, latency, throughput, failure modes) and comfort debugging with logs, metrics, and traces
Excellent communication and collaboration skills, with a track record of influencing decisions and mentoring other AI/ML practitioners

Job Responsibility

Design, build, and operate end-to-end AI/ML solutions (data pipelines, models, services, and tools) for diagnostics, prognostics, and test analytics
Implement production-grade ML pipelines on platforms such as Azure and Databricks, covering data ingestion, feature engineering, training, evaluation, and inference for batch and streaming workloads
Develop and maintain robust, observable ML services and internal tools that make complex vehicle and field data easy to use for engineers and technical stakeholders
Apply practical ML and statistical methods (e.g., tree-based models, time-series and anomaly detection, deep learning where appropriate) with a focus on reliability, explainability, and impact
Own model and data observability in production, including metrics, dashboards, alerts, and remediation workflows for drift, data quality, and performance regressions
Partner with data engineering to define and use industrialized and vectorized data products that support search, RAG, and analytics at scale
Review designs and code, mentor AI/ML practitioners, and help set high standards for testing, logging, deployment, and documentation
Collaborate with diagnostics/prognostics SMEs, validation, safety, and program teams to prioritize work, define success metrics, and embed solutions in day-to-day engineering workflows

Fulltime

Sr Machine Learning Engineer

Let’s do this. Let’s change the world. We are looking for a highly motivated exp...

Location

India , Hyderabad

Salary:

Not provided

Amgen

Expiration Date

Until further notice

Requirements

Hands-on experience with AWS, Databricks, Apache Spark, PySpark, SparkSQL, Python, and SQL for large-scale data engineering
Strong proficiency in workflow orchestration, Spark performance tuning, and scalable batch and streaming data pipeline development
Experience with real-time data processing and integration using Apache Kafka, Debezium, or similar streaming technologies
Hands-on experience with MLOps tools and practices, including MLflow, model serving, feature stores, experiment tracking, deployment, and lifecycle management
Experience with GenAI engineering practices, including prompt engineering, LLM evaluation, AI observability, agentic workflows, and knowledge graphs
Ability to design and develop APIs or service interfaces for data, ML, and GenAI application integration
Experience with Agile/SAFe delivery models, DevOps practices, CI/CD concepts, and cross-functional team collaboration
Strong analytical, problem-solving, debugging, communication, and teamwork skills
Ability to quickly learn, adapt, and apply emerging technologies across data, ML, and AI engineering
Doctorate degree / Master's degree / Bachelor's degree and 8 to 13 years of experience years of experience in Computer Science, IT or related field

Job Responsibility

Design, deploy, monitor, and optimize production-grade ML and Generative AI applications for AI-enabled manufacturing solutions
Define technical architecture, engineering standards, and best practices across data engineering, ML, GenAI, analytics, and platform capabilities
Partner with business stakeholders, product owners, and cross-functional teams to translate manufacturing challenges into secure, scalable, production-ready AI and data solutions
Design, develop, and maintain complex ETL/ELT pipelines in Databricks using PySpark, Scala, and SQL for large-scale structured and unstructured data processing
Build efficient ingestion, transformation, migration, and deployment pipelines across databases, APIs, logs, event streams, images, PDFs, documents, and third-party platforms
Design and implement GenAI solutions including RAG, embeddings, vector databases, agentic workflows, tool-calling systems, LLM orchestration, serving optimization, knowledge graphs, and metadata-driven retrieval
Build GenAI applications using frameworks and platforms such as LangChain, LangGraph, LlamaIndex, DSPy, OpenAI APIs, Amazon Bedrock, or equivalent technologies
Develop evaluation and observability frameworks to monitor model quality, hallucination rates, drift, retrieval effectiveness, latency, token usage, cost, reliability, operational health, and business impact
Build and maintain MLOps and LLMOps capabilities, including experiment tracking, model registry, prompt management, versioning, CI/CD, automated testing, deployment automation, monitoring, governance, and release controls
Design scalable data quality, validation, security, privacy, access control, logging, governance, and interoperability capabilities across hybrid cloud environments

Fulltime

Associate Machine Learning Engineer

The Associate Machine Learning Engineer position offers a unique opportunity to ...

Location

India , Hyderabad

Salary:

Not provided

Amgen

Expiration Date

Until further notice

Requirements

Any degree and 3 to 5 years of Computer Science, IT or related field experience
Strong foundations in machine learning algorithms and techniques
Experience in MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow)
Experience in model monitoring, including model observability and explainability
Proficiency in Python (or R) and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn)
Experience with big data technologies (e.g., Spark, Hadoop), and performance tuning in query and data processing
Understanding of the LLM inference lifecycle, including prompt execution, retrieval, and response generation
Awareness of common LLM failure modes such as hallucinations, prompt injection, and data leakage

Job Responsibility

Collaborate with data scientists to develop, train, and evaluate machine learning models
Build and maintain MLOps pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring
Leverage cloud platforms (AWS, Databricks) for ML model development, training, and deployment
Develop solutions using DevSecOps framework that are secure, scalable, reliable, and aligned with enterprise architecture standards
Evaluate model performance using appropriate metrics and optimize models for accuracy and efficiency
Develop and execute unit tests, integration tests, and other testing strategies to ensure the quality of the software
Create and maintain documentation on software architecture, design, deployment, disaster recovery, and operations
Identify and resolve technical challenges effectively
Provide ongoing support and maintenance for applications, ensuring that they operate smoothly and efficiently
Analyze customer feedback and support data to identify pain points and opportunities for improvement

Fulltime

Senior Machine Learning Engineer

Join Amgen’s Mission of Serving Patients. At Amgen, if you feel like you’re part...

Location

United States , Thousand Oaks

Salary:

158606.00 - 200052.00 USD / Year

Amgen

Expiration Date

Until further notice

Requirements

Bachelor’s degree (or foreign equivalent) in Computer Science, Statistics, Electrical Engineering, Mathematics, Bioengineering or a related field and 4 years of experience in the job offered or in a Data Scientist related – Occupation
4 years of experience in the following: 1) Programming skills in Python including experience with scientific computing and machine learning libraries including pandas, NumPy, scikit-learn, XGBoost, LightGBM, TensorFlow and PyTorch
2) Applying supervised and unsupervised learning techniques to real-world problems, including experience with Random Forest, XGBoost, ensemble models, and deep learning architectures
3) Version control (Git), containerization and orchestration tools including Docker and Kubernetes, and cloud environments including AWS or GCP
4) Involved with data science platforms including Databricks and SageMaker
5) Using statistical methods industry including regression modeling, hypothesis testing, Bayesian methods, Forecasting techniques and time-series analysis
6) Building ETL (Extract, Transform, Load) pipelines for handling large-scale, high-dimensional datasets, familiarity with healthcare data structures and data types
7) Experience with software DevOps CI/CD tools and GitLab
8) Experience developing and fine-tuning Natural Language Processing (NLP) models, including work with architectures such as BERT, ALBERT, GPT, and other transformer-based models.

Job Responsibility

Lead efforts with Amgen business leaders to identify, explore and develop transformative AI and ML solutions to enable access to computational tools and data within Amgen, and ultimately improve patient outcomes across multiple therapeutic areas
Utilize Cloud Services to collect, store, preprocess, and analyze large datasets from various sources across Amgen
Collaborate with other ML engineers, data scientists and research scientists to identify appropriate ML models and algorithms
Facilitate ML & Data engineering efforts by architecting and guiding the implementation of data and ML pipelines for development and deployment
Facilitate model deployment to production, including monitoring and maintenance of ML models, put in place metrics to assess accuracy and drift
Define model evaluation and validation strategies, train and test models, and analyze and resolve errors and biases in models
Lead and develop standards, processes, and best practices for the team across the machine learning-based solution implementation lifecycle
Involved in technical guide and career development mentor to junior machine learning engineers and data scientists in a formal or matrixed fashion.

What we offer

stock
retirement
medical
life and disability insurance
eligibility for an annual bonus or for sales roles, other incentive compensation
Retirement and Savings Plan with generous company contributions
group medical, dental and vision coverage
life and disability insurance
flexible spending accounts
discretionary annual bonus program

Fulltime

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Learning Process Engineer

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