senior data engineer

Atos

<div>
 
 About Atos
 
 
 
 Atos is a global leader in digital transformation with c. 78,000 employees and annual revenue of c. &euro; 10 billion. European number one in cybersecurity, cloud and high-performance computing, the Group provides tailored end-to-end solutions for all industries in 68 countries. A pioneer in decarbonization services and products, Atos is committed to a secure and decarbonized digital for its clients. Atos is a SE (Societas Europaea) and listed on Euronext Paris.
 
 
 The purpose of Atos is to help design the future of the information space. Its expertise and services support the development of knowledge, education and research in a multicultural approach and contribute to the development of scientific and technological excellence. Across the world, the Group enables its customers and employees, and members of societies at large to live, work and develop sustainably, in a safe and secure information space.
 
 
 
 Senior Data Engineer
 
 
 
 We are looking for a talented Data Engineer to join our team and play a pivotal role in transforming our data ecosystem. The ideal candidate will have extensive experience in handling data from diverse business areas and managing data sources from a range of commercial and custom tools. They should be proficient in data engineering technologies, including Snowflake, Talend (or similar ETL tools), and bring expertise in Python, dbt, and Airflow. Familiarity with API integrations and experience with Tableau or other data visualization tools would be an advantage.In this role, you will also work directly with business stakeholders, running workshops to gather requirements and convert them into actionable data solutions. Experience working in an agile environment is essential.
 
 
 
 Responsibilities
 
 
 
 Design, develop, and maintain ETL pipelines to extract, transform, and load data from various sources into our data warehouse.
 
 
 Collaborate with Data Analytics Product Owner and business stakeholders to understand data requirements and offer recommendations to improve data collection, processing, and analysis.
 
 
 Build and maintain data models to enable efficient SQL-based reporting and analysis.
 
 
 Implement data workflows and transformations using dbt, and orchestrate data pipelines with Airflow.
 
 
 Develop and maintain data integrations via APIs where necessary.
 
 
 Monitor, troubleshoot, and optimize data pipeline performance to ensure data accuracy, reliability, and availability.
 
 
 Collaborate with data engineers, data scientists, and analysts to develop data-driven solutions that drive business outcomes.
 
 
 
 Requirements
 
 
 
 Bachelor&rsquo;s degree in Computer Science, Information Systems, or a related field.
 
 
 5+ years of experience in data engineering.
 
 
 Proficiency with data management tools like Snowflake, Talend, or similar ETL tools.
 
 
 Strong experience with Python, dbt, and Airflow.
 
 
 Solid understanding of SQL and database design.
 
 
 Knowledge of API integrations.
 
 
 Experience with Tableau or other data visualization tools (nice to have).
 
 
 Demonstrated ability to work independently and within a collaborative team environment.
 
 
 Strong analytical and problem-solving skills.
 
 
 Excellent communication and interpersonal skills.
 
 
 English fluency is required; proficiency in French is a plus.
 
 
 Here at Atos, diversity and inclusion are embedded in our DNA. Read more about our commitment to a fair work environment for all.
 
 
 Atos is a recognized leader in its industry across Environment, Social and Governance (ESG) criteria. Find out more on our CSR commitment.
 
 
 
 Choose your future. Choose Atos.
 
</div>

SENIOR DATA ENGINEER

Payrails

<div>
 
 About Payrails
 
 
 
 Payrails is a global payment software company helping leading enterprises to take control of their payment operations and maximize performance. With deep experience in the payments space and firsthand knowledge of merchants' challenges, we&rsquo;ve seen how fragmented, complex, and inefficient these systems can become. Now, we are setting a new industry standard for how enterprises around the world manage and optimize payments, with more control, visibility and flexibility than ever before.
 
 
 Our vision is to reimagine payments from the ground up. We are building a deeply integrated meta layer that spans the entire payment lifecycle with a modular architecture. This helps us give leading brands building blocks to craft solutions to most complex operational challenges, tailor seamless customer experiences and grow their business.
 
 
 We are backed by some of the world&rsquo;s top investors including Andreessen Horowitz, HV Capital, EQT Ventures and General Catalyst, who share our mission to simplify payment complexity globally.
 
 
 At Payrails, we&rsquo;re committed to building a team of exceptional people - not just talented, but driven to build, solve, and deliver at the highest level. Excellence isn&rsquo;t just a value here; it&rsquo;s a way of working. We believe that great people thrive in environments where there&rsquo;s trust, clarity, and shared purpose. We work openly and collaboratively, with deep respect for each other&rsquo;s craft. Everyone is encouraged to understand the bigger picture - what we&rsquo;re building, why it matters, and what stands in the way. When people have that context, they move faster, take ownership, and make better decisions. We care about creating a culture where people feel inspired to do their best work and a deep sense of responsibility to help us bring our vision to life. Success at Payrails means staying focused on the problems that matter most, and executing with purpose.
 
 
 
 
 Your team
 
 
 
 
 At Payrails, data is at the core of everything we do. We don&rsquo;t just analyze data; we turn it into actionable insights that fuel smarter decision-making and drive the future of our products. As we continue to revolutionize the payments industry we are seeking an exceptional Senior Data Engineer to help us in our mission.
 
 
 Our Data Team is at the forefront of driving transformation, empowering every department to unlock the full potential of data
 
 
 
 
 How you will make an impact
 
 
 
 
 <ul>
 <li>
 Work alongside a talented team of analysts, data scientists and engineers to build data products and services that meet business requirements.
 </li>
 <li>
 Design, develop and maintain robust, scalable and observable batch and real-time data pipelines.
 </li>
 <li>
 Architect, build and maintain the data infrastructure at Payrails.
 </li>
 <li>
 Advocate for and implement data governance and security best practices.
 </li>
 <li>
 Contribute to tooling that improves data quality, CI/CD workflows, and data observability.
 </li>
 <li>
 Collaborate with cross-functional teams to understand requirements and design optimal solutions.
 
 
 </li>
 </ul>
 
 
 What we are looking for
 
 
 
 
 <ul>
 <li>
 You have extensive experience in data engineering roles building reliable, scalable and observable production-grade data pipelines and services.
 </li>
 <li>
 You have strong proficiency in Python. Experience with GoLang is a plus.
 </li>
 <li>
 You are proficient in SQL, data modelling and operating common OLTP (e.g. PostgresSQL) and OLAP databases (e.g. Snowflake, Bigquery) at scale.
 </li>
 <li>
 You develop and maintain data pipelines using workflow management platforms such as Apache Airflow.
 </li>
 <li>
 You are knowledgeable of containerization technologies such as Docker and container orchestration platforms like Kubernetes.
 </li>
 <li>
 You communicate effectively and are proficient in English.
 </li>
 <li>
 You work independently and collaboratively in a fast-paced environment.
 </li>
 <li>
 Experience with real-time streaming technologies (e.g. Kafka, Kinesis) and distributed stream processing technologies (e.g. Apache Flink, Apache Beam, Kafka Streams) is an advantage.
 </li>
 <li>
 Familiarity working with infrastructure as code (e.g. Terraform) is preferred.
 </li>
 <li>
 FinTech or payments domain experience is a plus.
 
 
 </li>
 </ul>
 
 
 What we offer
 
 
 
 
 <ul>
 <li>
 High impact and high velocity environment with the most talented and ambitious people you will ever work with
 </li>
 <li>
 A chance to shape the story of a company and a category from the ground up
 </li>
 <li>
 Real ownership. You&rsquo;ll have the freedom and trust to build, test, and take lead
 </li>
 <li>
 A product used by the best brands around the world
 </li>
 <li>
 Hybrid working with an office in the heart of New Cairo
 </li>
 <li>
 Regular team events, activities and off-sites
 </li>
 <li>
 Competitive salary and equity package
 </li>
 <li>
 27 days of annual paid vacation
 
 
 </li>
 </ul>
</div>

Senior Data Engineer

EVA pharma

<div>
 
 Join EVA Pharma, a leading pharmaceutical company dedicated to empowering the fight for&nbsp;Health and well-being as a fundamental human right. Recognized and certified as a best place to work, we are committed to fostering a supportive and innovative environment for&nbsp;our team members.
 
 
 
 Job Summary:
 
 
 We are seeking a passionate and talented
 
 Data Engineer Senior Lead
 
 to join our dynamic team. The&nbsp;ideal candidate will contribute to our mission of enhancing human health and well-being,&nbsp;ensuring that we meet the highest standards of excellence in our industry.
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Design, develop, and maintain reliable ETL/ELT pipelines that move data from multiple sources into cloud-based warehouses such as Snowflake, BigQuery, or Databricks. Ensure real-time or near-real-time data processing for analytics dashboards and operational systems. Continuously fine-tune performance to handle growing data volumes efficiently
 </li>
 <li>
 Implement automated validation checks, anomaly detection, and alerting systems to maintain high data accuracy. Ensure all pipelines comply with data privacy and security standards (e.g., GDPR, SOC 2). Maintain clear documentation and data lineage to support audits and cross-team visibility
 </li>
 <li>
 Evaluate and introduce new tools like Airflow, dbt, Kafka, or Spark to improve efficiency and scalability. Collaborate with AI/ML teams to enable deployment and integration of advanced models
 </li>
 <li>
 Develop best practices for data modeling, storage optimization, and version control. Align data structures with key business metrics and analytics use cases to ensure consistency across departments
 </li>
 <li>
 Conduct design reviews, ensure high-quality code, and promote a collaborative culture focused on innovation and continuous improvement. Also, Mentor and coach data engineers to enhance their technical skills and improve project execution
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 <ul>
 <li>
 Bachelor's degree in Data Science, Computer Science, Statistics, or a related field
 </li>
 <li>
 7-10 years of experience in data engineering or related fields, with at least 2 years in a leadership role
 </li>
 <li>
 Proven ability to design, build, and optimize scalable ETL/ELT pipelines and data workflows for analytics and operational use
 </li>
 <li>
 Strong skills in SQL and Python, with hands-on experience in cloud-based data platforms and distributed systems
 </li>
 <li>
 Deep understanding of data modeling, data warehousing, orchestration tools (e.g., Airflow, Prefect), and big data technologies such as Spark and Databricks
 </li>
 <li>
 Solid grasp of data governance, privacy, and security best practices, combined with strong problem-solving, architectural design, and cross-functional collaboration abilities
 </li>
 </ul>
</div>

Senior Data Engineer Lead

Interact Technology Solutions

<div>
 
 Job Summary
 
 
 
 The
 
 Senior AI Data Engineer
 
 is responsible for designing, building, and optimizing enterprise-scale data and AI infrastructure to support machine learning models, generative AI applications, and real-time analytics. The role drives the development of end-to-end data pipelines, from ingestion to production-ready AI data products, ensuring scalability, performance, and compliance across multi-cloud environments.
 
 
 
 Accountability &amp; Responsibilities
 
 
 
 <ul>
 <li>
 Design, build, and maintain scalable ETL/ELT data pipelines using modern data engineering tools (e.g., Apache Spark, dbt).
 </li>
 <li>
 Architect and implement Lakehouse data platforms (Delta Lake, Apache Iceberg, Apache Hudi) following Medallion architecture (Bronze/Silver/Gold).
 </li>
 <li>
 Develop real-time streaming pipelines using Apache Kafka, Apache Flink, and Spark Structured Streaming.
 </li>
 <li>
 Build and optimize AI/GenAI data pipelines for LLM training, fine-tuning, and inference (tokenization, dataset curation, prompt engineering datasets).
 </li>
 <li>
 Design and implement Retrieval-Augmented Generation (RAG) pipelines, including embedding workflows and vector database integration.
 </li>
 <li>
 Manage feature stores for real-time and batch machine learning use cases.
 </li>
 <li>
 Integrate data pipelines with AI/ML platforms (Databricks MLflow, Azure ML, AWS SageMaker, Vertex AI, OpenAI/Azure OpenAI).
 </li>
 <li>
 Implement data orchestration workflows using Apache Airflow or similar tools with CI/CD pipelines.
 </li>
 <li>
 Ensure data quality, governance, and security using frameworks such as Great Expectations and data catalog tools.
 </li>
 <li>
 Deploy and manage infrastructure using Infrastructure-as-Code tools (Terraform, Bicep, CDK).
 </li>
 <li>
 Collaborate with Data Scientists, ML Engineers, and Solution Architects to deliver production-ready AI solutions.
 </li>
 <li>
 Lead technical design decisions, mentor junior engineers, and contribute to data platform strategy.
 </li>
 <li>
 Maintain documentation, data contracts, and operational runbooks for all pipelines.
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 1
 
 &ndash; Required Experience
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Engineering, or related field.
 </li>
 <li>
 4&ndash;5 years of experience in data engineering, with strong exposure to AI/ML data infrastructure.
 </li>
 <li>
 Proven experience building scalable data pipelines and working with large-scale datasets.
 </li>
 <li>
 Hands-on experience with AI/ML platforms and modern data architectures.
 </li>
 <li>
 Experience in regulated industries (e.g., Banking, Telecom, Healthcare) is a plus.
 </li>
 <li>
 Strong problem-solving, analytical thinking, and communication skills.
 </li>
 <li>
 Experience working in cross-functional teams and agile environments.
 
 
 </li>
 </ul>
 
 2&ndash; Technical Skills
 
 
 
 <ul>
 <li>
 Strong SQL and advanced data modeling techniques
 </li>
 <li>
 Apache Spark (PySpark, Spark SQL, Streaming)
 </li>
 <li>
 Python (pandas, PySpark, data processing libraries)
 </li>
 <li>
 Data pipeline orchestration (Apache Airflow)
 </li>
 <li>
 CI/CD for data pipelines (GitHub Actions / Azure DevOps)
 </li>
 <li>
 Lakehouse architectures (Delta Lake / Iceberg / Hudi)
 </li>
 <li>
 Streaming technologies (Kafka, Flink)
 </li>
 <li>
 Cloud platforms (AWS / Azure / GCP)
 </li>
 <li>
 Vector databases (Pinecone, Weaviate, pgvector, OpenSearch)
 </li>
 <li>
 RAG pipeline design and LLM data processing
 </li>
 <li>
 Infrastructure-as-Code (Terraform / Bicep / CDK)
 </li>
 <li>
 Containers (Docker, Kubernetes)
 </li>
 <li>
 Data quality &amp; governance tools
 </li>
 </ul>
</div>

Senior AI Data Engineer

sonnen Egypt

<div>
 
 Standort
 
 
 
 Cairo, EG
 
 
 
 Stellen-ID
 
 : 4758
 
 
 Join the energy revolution with #teamsonnen!
 
 
 At sonnen, we&rsquo;re driven by a clear goal: creating a future powered by clean, affordable energy for everyone. That&rsquo;s why we make our customers independent &ndash; not only from fossil fuels, but also from rising electricity costs.
 
 
 The key to this independence is our intelligent, all-in-one energy system. It combines solar panels, battery storage, energy tariffs, and wallboxes &ndash; all developed and manufactured in Germany.
 
 
 As the first and only provider in Germany, we also connect thousands of home batteries into one shared network: the sonnenVPP, our industry-leading virtual power plant.
 
 
 In short: every day, we&rsquo;re working to shape the energy future. And we&rsquo;d be thrilled to have you join us!
 
 
 We are seeking a Data Engineer (m/f/d) to join our team and play a pivotal role in enabling our Business Intelligence and Data Science teams. As a Data Engineer, you will be responsible for maintaining and enhancing our AWS-based analytics platform, provisioning data from various sources, and enabling the development and stable operation of analytical solutions. We&rsquo;re looking for someone who shares our values, who isn&rsquo;t afraid to challenge existing processes, and who would like to work on innovative solutions in a fast-moving environment. If this sounds like you, then don&rsquo;t hesitate to get in touch.
 
 
 
 What you will do to help drive the energy transition:
 
 
 
 <ul>
 <li>
 (Senior) Define and design the architecture of our analytics platform, ensuring scalability, performance, and reliability.
 </li>
 <li>
 You design and build scalable data pipelines, ETL processes, and data lake and data warehousing solutions to support our analytics solutions.
 </li>
 <li>
 You develop and maintain data integration processes with a variety of structured and unstructured data sources.
 </li>
 <li>
 You implement, test, and maintain infrastructural components of sonnen&rsquo;s analytics platform and deploy and maintain data models.
 </li>
 <li>
 You implement data quality checks and monitoring mechanisms to ensure accuracy, completeness, and consistency of data.
 </li>
 <li>
 You define coding principles and support data scientists and analysts in implementing algorithms into operational solutions.
 </li>
 <li>
 Adhere to stringent quality assurance and documentation standards, utilizing version control and code repositories such as Gitlab.
 </li>
 <li>
 You stay up to date with emerging trends and technologies in data engineering and assess their potential applications to our business needs.
 </li>
 <li>
 (Senior) Share your knowledge by coaching/pair coding with more junior engineers.
 
 
 </li>
 </ul>
 
 What You Will Need On That Journey
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in computer science or a related technical field.
 </li>
 <li>
 +3 years of relevant employment experience in roles such as Data Scientist, Data Engineer, or Data Architect.
 </li>
 <li>
 +3 years of experience with ETL tools, Data Modeling, and Data Architecture.
 </li>
 <li>
 Experience with Big Data technologies such as Hadoop, Hive, and Spark.
 </li>
 <li>
 Ability to translate organizational goals into technical solutions.
 </li>
 <li>
 Experience with Infrastructure as Code (experience in Terraform and Ansible are a plus).
 </li>
 <li>
 Proficiency in Python, SQL, and NoSQL.
 </li>
 <li>
 Excellent communication and project management skills.
 
 
 </li>
 </ul>
 
 Stellensegment:
 
 Quality Assurance, Computer Science, Data Warehouse, Business Intelligence, Database, Technology
</div>

Data Engineer (m/f/d)

Halan - حالا

<div>
 
 Job Overview:
 
 
 We are seeking a talented and motivated Senior Data Engineer with expertise in Scala and Python to join our data engineering team. This individual will play a key role in the design, development, and optimization of our data infrastructure and data pipelines. The ideal candidate has a passion for building scalable, high-performance systems and is eager to broaden their knowledge across the entire data engineering stack, from hardware infrastructure to project development.
 
 
 Key responsibilities:
 
 
 &bull; Collaborate with cross-functional teams to design, develop, and maintain data engineering solutions using Scala, Python, and Apache Spark.
 
 
 &bull; Implementation of new data engineering technologies, frameworks, and tools, such as HDFS, MongoDB, and PostgreSQL, to enhance performance, scalability, and efficiency.
 
 
 &bull; Understand and optimize hardware and resource consumption for data engineering projects.
 
 
 &bull; Develop a deep understanding of hardware infrastructure, including servers, clusters, and distributed systems, to ensure optimal data processing and storage.
 
 
 &bull; Design and architect high-performance, fault-tolerant, and scalable data pipelines.
 
 
 &bull; Conduct research and stay current with the latest advancements in data engineering, hardware technologies, and distributed computing paradigms.
 
 
 &bull; Mentor and guide junior team members, fostering a culture of continuous learning and skill development.
 
 
 &bull; Collaborate with stakeholders to gather requirements, propose technical solutions, and deliver high-quality data engineering projects.
 
 
 Requirements:
 
 
 &bull; 2-3 years of professional experience as a Software Engineer, with a focus on data engineering.
 
 
 &bull; Keen interest in hardware infrastructure, resource consumption optimization, and data engineering project development.
 
 
 &bull; Proven ability to work effectively in an Agile development environment and manage multiple priorities.
 
 
 &bull; Strong problem-solving, analytical thinking, communication, and collaboration skills.
 
</div>

Data Engineer

Siemens

<div>
 
 About Brightly
 
 
 
 Brightly is a global leader in intelligent, cloud‑based asset lifecycle management, empowering 12,000+ clients with predictive insights to optimize maintenance, energy, and capital planning&mdash;backed by Siemens. Our products help schools, hospitals, cities, and manufacturers keep critical infrastructure running efficiently and sustainably.
 
 
 
 The Opportunity
 
 
 
 We&rsquo;re looking for a Senior Machine Learning Engineer to lead LLM‑powered application development&mdash;from prototype to production&mdash;on AWS. You&rsquo;ll design robust ML/LLM services that power search, recommendations, copilots, and workflow automation in Brightly&rsquo;s platform, partnering closely with product, data, and engineering teams. Responsibilities and skill expectations reflect current industry practice for senior ML/LLM engineers, including end‑to‑end model lifecycle ownership, production‑grade code, and MLOps.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Build LLM applications: Design and implement RAG pipelines, prompt orchestration, tools/agents, safety/guardrails, and evaluation harnesses; instrument for latency, cost, and quality. (Guided by current LLM engineer role practices.)
 </li>
 <li>
 Own the ML lifecycle: Data curation, feature engineering, training/fine‑tuning (LoRA/QLoRA), A/B testing, deployment, monitoring, and continuous improvement of models and prompts.
 </li>
 <li>
 Productionize on AWS: Ship scalable services on EKS/ECS/Lambda; leverage SageMaker, Bedrock, EMR, MSK, Step Functions; apply observability (CloudWatch/OpenTelemetry) and cost controls. (Duties aligned to modern AWS ML roles.)
 </li>
 <li>
 Scale training &amp; inference: Use distributed training (FSDP/DeepSpeed), quantization, caching, vector databases, and GPU/Inferentia for performance and efficiency.
 </li>
 <li>
 MLOps &amp; governance: Establish CI/CD for models (MLflow/Kedro/SageMaker Pipelines), model/version registries, data and prompt lineage, evaluation gates, and responsible‑AI controls. (Aligned with contemporary MLOps templates.)
 </li>
 <li>
 Partner across Brightly: Translate asset‑management use cases into ML/LLM solutions; collaborate with product managers and UX to ship customer‑visible features that measurably improve reliability, safety, and sustainability.
 </li>
 <li>
 Mentor &amp; lead: Provide technical leadership, review designs/PRs, and raise the bar on ML engineering excellence across the team. (Common senior ML expectations.)
 </li>
 <li>
 Perform Exploratory Data Analysis (EDA) on structured, semi‑structured, and unstructured datasets to identify patterns, correlations, feature importance, and data quality issues.
 
 
 </li>
 </ul>
 (Consistent with ML engineer responsibilities to analyze data before model development.)
 
 
 <ul>
 <li>
 Conduct deep research on asset-related, operational, and domain-specific datasets to understand root causes, trends, and predictive signals.
 
 
 </li>
 </ul>
 
 What You&rsquo;ll Bring
 
 
 
 
 Required experience
 
 
 
 <ul>
 <li>
 5&ndash;7 years total software/ML engineering experience, with 3+ years building and operating ML systems in production.
 </li>
 <li>
 1+ years hands‑on LLM application development (e.g., RAG, fine‑tuning, prompt engineering, evaluators/guardrails, agentic workflows) using packages such as Langchain and Langgraph.
 </li>
 <li>
 AWS proficiency (3+ years): Strong with core services (EKS/ECS, Lambda, S3, DynamoDB/RDS, Step Functions, IAM) and ML stack (SageMaker, Bedrock or HF on AWS). (Representative AWS ML role skills.)
 </li>
 <li>
 Modeling &amp; frameworks: Python, PyTorch, Hugging Face ecosystem; vector stores (e.g., OpenSearch, PGVector, Pinecone), embeddings, retrieval, and evaluation metrics for NLP/LLMs. (In line with senior LLM roles.)
 </li>
 <li>
 MLOps: CI/CD for ML, model registries, experiment tracking, telemetry/monitoring, automated retraining; Docker/Kubernetes, GitHub Actions/GitLab CI. (Current MLOps expectations.)
 </li>
 <li>
 Data engineering fluency: ETL/ELT, streaming/batch (Spark/Flink), data quality and governance controls for ML.
 
 
 </li>
 </ul>
 
 Nice to have
 
 
 
 <ul>
 <li>
 Experience with distributed training (FSDP, DeepSpeed), RLHF, or Inferentia/Trainium optimization.
 </li>
 <li>
 Exposure to sustainability/asset/intelligent operations domains.
 </li>
 <li>
 Familiarity with security &amp; compliance for ML systems in enterprise environments. (Frequently included in senior ML roles.)
 
 
 </li>
 </ul>
 How you&rsquo;ll work
 
 
 <ul>
 <li>
 Pragmatic and product‑oriented: You bias to measurable outcomes and iterate quickly with stakeholders. (Modern senior ML role framing.)
 </li>
 <li>
 Engineering excellence: You write production‑quality Python, design reliable APIs/services, and uphold testing/observability standards. (Common duties in senior templates.)
 </li>
 <li>
 Collaborative leadership: You mentor peers and influence architecture across teams. (Industry‑standard senior expectations.)
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s in CS/EE/Math or related field (Master&rsquo;s preferred) or equivalent practical experience. (Typical for senior ML roles.)
 
 
 </li>
 </ul>
 Join a mission‑driven team building technology that keeps communities running&mdash;safer, greener, and more resilient&mdash;at global scale. You&rsquo;ll pair startup‑speed product work with the reach and rigor of Siemens.
 
 
 
 The Brightly culture
 
 
 
 We&rsquo;re guided by a vision of community that serves the ambitions and wellbeing of all people, and our professional communities are no exception. We model that ideal every day by being supportive, collaborative partners to one another, conscientiously making space for our colleagues to grow and thrive. Our passionate team is driven to create a future where smarter infrastructure protects the environments that shape and connect us all. That brighter future starts with us.
</div>

Senior Machine Learning Engineer

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