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Internship Remote Design Verification Engineer Jobs in Wisconsin

Qualysoft

Hybrid - ca. 50 % vor Ort in Wien, ca. 50 % remote Projektsprache: Deutsch und Englisch Aufgaben: ... API- und Schnittstellendesign, Orchestrierung mit Azure Functions und Logic Apps) Aufbau und ...

Qualysoft

... 50 % remote Projektsprache: Deutsch und Englisch Aufgaben: Konzeption, Entwicklung und ... verification signals in application materials based on available information. These tools assist ...

Wisconsin

Software Engineer/Developer III

Madison, WI · On-site +1

$90K/yr

Remote work is an option for this position on a voluntary basis; however, it is important to note ... Reviews application design specifications, codes new applications, and makes enhancements to ...

Qualysoft

Vienna (1-2 days on-site per week; otherwise remote) Start: ASAP Duration: 12 months (extension ... We are looking for a Frontend Developer with a strong focus on UI/UX design and implementation

Resource Innovations

Energy Engineer

Madison, WI · On-site +1

This position may be remote, with a preferred location in Illinois, Iowa, Massachusetts, New Jersey ... Conduct measurement and verification activities to establish facility operating conditions, confirm ...

Resource Innovations

Energy Engineer

Madison, WI · On-site +1

This position may be remote, with a preferred location in Illinois, Iowa, Massachusetts, New Jersey ... Conduct measurement and verification activities to establish facility operating conditions, confirm ...

Hikinex

$111K - $152K/yr

REMOTE OR HYBRID IS POSSIBLE FOR THE RIGHT CANDIDATE. Open for candidates in Canada as well as the ... Review payload, platform, and subsystem design; including block diagrams, ICDs, ConOps, and ...

Hikinex

REMOTE OR HYBRID IS POSSIBLE FOR THE RIGHT CANDIDATE. Open for candidates in Canada as well as the ... to design and develop Test Plans for Satellites and Payloads, aligning with verification ...

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Internship Remote Design Verification Engineer information

What is the difference between Internship Remote Design Verification Engineer vs Internship Remote Test Engineer?

AspectInternship Remote Design Verification EngineerInternship Remote Test Engineer
Primary FocusVerifying hardware or chip designs against specificationsTesting software or hardware products for functionality and performance
Required SkillsHardware design, verification methodologies, scriptingTesting procedures, scripting, debugging
Work EnvironmentDesign labs, remote collaboration with design teamsTesting labs, remote testing environments
Common Industry UsageSemiconductor, electronics companiesSoftware, electronics, consumer electronics companies

While both roles involve testing and verification, the Design Verification Engineer focuses on ensuring hardware or chip designs meet specifications, whereas the Test Engineer emphasizes testing products for functionality. Internships in both areas provide valuable experience in verification and testing processes within the tech industry.

What are the key skills and qualifications needed to thrive as an internship remote design verification engineer, and why are they important?

To succeed as an Internship Remote Design Verification Engineer, you need a solid understanding of digital design concepts, logic circuits, and proficiency in hardware description languages like Verilog or VHDL, often gained through coursework or related internships. Familiarity with simulation tools (such as ModelSim or Synopsys VCS) and version control systems is typically required, and knowledge of scripting languages like Python or TCL is a plus. Strong analytical thinking, effective communication, and attention to detail are crucial soft skills for collaborating with remote teams and identifying design issues. These skills enable accurate verification, efficient teamwork, and the delivery of reliable hardware solutions in a distributed work environment.

What does an internship remote design verification engineer do?

An Internship Remote Design Verification Engineer assists in verifying and validating the functionality of hardware designs, typically for integrated circuits or systems on chip (SoC). Working remotely, they collaborate with engineering teams to develop test plans, create simulation environments, and run verification tests to ensure designs meet required specifications. Interns in this role learn industry-standard verification methodologies such as UVM and tools like SystemVerilog, and contribute to debugging and documenting design issues. The role provides practical experience in hardware design, verification processes, and remote teamwork within the semiconductor industry.

Are verification engineers in demand?

Verification engineers, including design verification engineers, are in high demand due to the increasing complexity of electronic systems and the need for thorough testing. Skills in hardware description languages like VHDL or Verilog, along with experience in simulation tools, enhance employability in this field.

What are some common challenges faced by remote design verification engineering interns, and how can they overcome them?

Remote design verification engineering interns often face challenges such as limited face-to-face mentorship, time zone differences, and communication barriers with team members. To overcome these, it's important to proactively schedule regular check-ins with mentors, make use of collaborative tools (like Slack or Zoom), and document questions or issues clearly before reaching out for help. Staying organized and setting clear daily or weekly goals can also help interns stay on track and maximize their learning experience in a remote environment.

How much does a design verification engineer earn?

A remote design verification engineer typically earns between $70,000 and $120,000 annually, depending on experience, location, and industry. Entry-level positions may start lower, while experienced engineers with specialized skills or certifications can earn higher salaries, especially in high-demand sectors like semiconductor or hardware design.
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Internship Remote Design Verification Engineer jobs near you

Databricks AI / ML Engineer (m/w/d)

Qualysoft

On-site, Remote

Contractor

Re-posted 8 days ago

Job description

Fur ein langfristig angelegtes Daten- und KI-Programm wird ein Databricks AI / ML Engineer (m/w/d) gesucht.
Ziel ist die Entwicklung, Implementierung und der Betrieb skalierbarer Machine-Learning- und LLM-Losungen auf Azure Databricks von der Datenaufbereitung uber Feature Engineering bis hin zu MLOps, Deployment und Monitoring.
Der Fokus liegt auf Big-Data-Engineering, ML/LLM-Workloads, MLOps-Automatisierung sowie der nahtlosen Integration in das Microsoft-Okosystem.
520 - 560 a day
Rahmenbedingungen
Start: Marz/April 2026
Laufzeit: 3 Jahre (optional verlangerbar bis max. 5 Jahre)
Auslastung: 100 %
Arbeitsmodell: Hybrid - ca. 50 % vor Ort in Wien, ca. 50 % remote
Projektsprache: Deutsch und Englisch

Aufgaben:
Datenanalyse und Prototyping mit Python in Azure Databricks unter Einsatz gangiger ML-Frameworks
Entwicklung und Betrieb von Big-Data-Pipelines mit Apache Spark, Delta Lake und Databricks SQL
Durchfuhrung von Feature Engineering sowie Training, Versionierung und Deployment von Modellen mit Databricks MLflow
Entwicklung und Betrieb von ML- und LLM-Workloads auf Azure Databricks (inkl. Unity Catalog, Performance- und Kostenoptimierung)
End-to-End-Integration der Losungen in das Microsoft-Okosystem (z. B. API- und Schnittstellendesign, Orchestrierung mit Azure Functions und Logic Apps)
Aufbau und Weiterentwicklung von MLOps- und CI/CD-Pipelines fur automatisiertes Training, Testing, Deployment und Monitoring von ML- und LLM-Modellen sowie Agents
Durchfuhrung von Modell- und Datenmonitoring (Modellleistung, Daten-Drift, Bias) inklusive Wartungs- und Updateprozessen
Einsatz von AutoML-Tools zur Beschleunigung von Prototypen und Experimenten
Sicherstellung von Skalierbarkeit, Sicherheit und stabilen Betriebsprozessen der entwickelten Losungen

Fachliche Anforderungen:
Fundierte Kenntnisse in Datenanalyse und Prototyping mit Python in Azure Databricks
Erfahrung mit Machine-Learning-Frameworks wie TensorFlow, PyTorch und scikit-learn
Praktische Erfahrung im Big Data Engineering mit Apache Spark, Delta Lake und Databricks SQL
Kompetenz in Feature Engineering sowie Modell-Deployment mit managed Databricks MLflow
Erfahrung in der Entwicklung und dem Betrieb von ML- und LLM-Workloads auf Azure Databricks
Erfahrung mit End-to-End-Integrationen im Microsoft-Okosystem
Erfahrung im Aufbau von MLOps- und CI/CD-Pipelines fur ML- und LLM-Modelle sowie agentische Workflows
Erfahrung im Modell- und Datenmonitoring (Leistung, Drift, Bias) inklusive passender Wartungsstrategien
Praktische Erfahrung im Einsatz von AutoML-Tools
Vorhandensein einer eigenen, vom Produktivsystem des Auftraggebers getrennten Entwicklungsumgebung, die den aktuellen Standards fur Datensicherheit und Zugriffsschutz entspricht (inkl. Nachweis der Infrastruktur)

PLUS:
Erfahrung mit Data- und KI-Governance
Erfahrung in der Konzeption und Umsetzung agentischer Ansatze (Agenten, Multi-Agent-Systeme, agentische Workflows) mit Azure-Ressourcen
Erfahrung in der Umsetzung von End-to-End-Databricks-Projekten (von Datenaufbereitung und Feature Engineering uber Modelltraining und Deployment bis zu MLOps und Monitoring)
Branchenkenntnisse in der Energieindustrie
Strukturierte und analytische Arbeitsweise
Hohes Qualitatsbewusstsein und Verantwortungsbereitschaft
Sehr gute Kommunikationsfahigkeit gegenuber technischen und fachlichen Stakeholdern
Teamfahigkeit und Bereitschaft zur Wissensweitergabe

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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