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Job description: We are seeking a talented, tenacious, results driven individual to work in a multi-disciplinary R&D environment with likeminded motivated electrical engineers, mathematicians, and computer scientists who are collectively responsible for creating custom geolocation and digital communications systems in support of national security defense. Core responsibilities include creative problem solving, researching or inventing advanced geolocation algorithms, implementing them in efficient software, testing with real-world data, and deploying to front-line customer facilities. Our dynamic environment and diverse projects demand flexibility to learn new technologies quickly. Our personnel can expect to work across all functional areas: systems engineering, development, integration and test, deployment and O&M. Core responsibilities include: Design/architect, develop, test, deploy, and operate fully integrated software Design, build, and maintain infrastructure for modern integration between our applications and third-party services Collaborate extremely effectively with product managers, designers, other engineers, stakeholders, and vendors on projects within the team. Communicate technical ideas and work closely with other senior members of the team. You will also provide technical leadership and guidance to junior team members and mentor others to grow in their technical abilities. A key responsibility is staying up-to-date with the latest technologies, tools, and methodologies and experimenting with new technologies to incorporate innovative solutions into our projects. Our personnel can expect to work across all functional areas: systems engineering, development, integration and test, deployment and O&M, and experience the direct mission feedback from the customer and seeing your project provide real-world contributions that make a significant difference. Youre encouraged and expected to propose things that you believe will improve the applications and frameworks youre working in. The ability to work unsupervised with minimal direction and the ability to self-start is a must. What required background will make you successful? Expert knowledge of data structures, algorithms, and modern design patterns and data layers Expert knowledge of Golang Passion to build internal solutions and own development of enterprise-wide applications Extensive knowledge of building quality APIs for internal and external products Extensive experience integrating internal and third-party services into your solution Highly proficient in modern software engineering practices for testability and readability Demonstrated ability to design the architecture of software systems to ensure they achieve functionality, performance, scalability, and maintainability requirements Degree (Bachelor's, Master's, or PhD) in Computer Engineering or Computer Science Minimum 15 years' experience in software engineering-related discipline Active TS/SCI security clearance US CITIZENSHIP REQUIRED Preferred skills: Experience providing technical leadership and guidance to junior team member and mentoring other engineers to grow in their technical abilities Highly proficient in C++ and Python for engineering and scientific applications in LINUX environments Knowledge of cloud computing platforms like Amazon Web Services (AWS) Knowledge of Javascript and web technologies such as VueJS or React Experience automating workflows across the enterprise DevOps and Cloud computing Experience (Gitlab, CI/CD, CVE mitigations, Docker, Kubernetes, PIP) Agile development processes and leadership Full relocation provided Remote work/telework is not available for this position. Qualifications: What required background will make you successful? Expert knowledge of data structures, algorithms, and modern design patterns and data layers Expert knowledge of Golang Passion to build internal solutions and own development of enterprise-wide applications Extensive knowledge of building quality APIs for internal and external products Extensive experience integrating internal and third-party services into your solution Highly proficient in modern software engineering practices for testability and readability Demonstrated ability to design the architecture of software systems to ensure they achieve functionality, performance, scalability, and maintainability requirements Degree (Bachelor's, Master's, or PhD) in Computer Engineering or Computer Science Minimum 15 years' experience in software engineering-related discipline Active TS/SCI security clearance US CITIZENSHIP REQUIRED Preferred skills: Experience providing technical leadership and guidance to junior team member and mentoring other engineers to grow in their technical abilities Highly proficient in C++ and Python for engineering and scientific applications in LINUX environments Knowledge of cloud computing platforms like Amazon Web Services (AWS) Knowledge of Javascript and web technologies such as VueJS or React Experience automating workflows across the enterprise DevOps and Cloud computing Experience (Gitlab, CI/CD, CVE mitigations, Docker, Kubernetes, PIP) Agile development processes and leadership Full relocation provided Remote work/telework is not available for this position. Why is This a Great Opportunity: We are seeking a talented, tenacious, results driven individual to work in a multi-disciplinary R&D environment with likeminded motivated electrical engineers, mathematicians, and computer scientists who are collectively responsible for creating custom geolocation and digital communications systems in support of national security defense. Salary Type : Annual Salary Salary Min : $ 160000 Salary Max : $ 260000 Currency Type : USD

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About the team, this team that powers Elsevier's Health platforms: Clinical Key AI, Sherpath AI, and AI-driven automated clinical and content workflows. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world's largest medical and scholarly landscapes. About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality. Key Responsibilities ML & LLM Engineering, Search and Recommendation Engines Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI). Maintain and version model registries and artifact stores to ensure reproducibility and governance. Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML. Scale end-end custom Sagemaker pipelines. Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hosted. Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs . Build evaluation pipelines: offline IR metrics (NDCG, MAP, MRR), LLM quality metrics (faithfulness, grounding), and A/B testing. Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization. Stay current with the latest GAI research, NLP and RAG and apply the state-of-the-art in our experiments and systems. Collaboration Partner with Subject-Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions Collaborate and interface with Operations Engineers who deploy and run production infrastructure. Qualifications Current experience in ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production. Strong Python, Java, and/or Scala experience will be considered a plus. Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google) Experience with Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr / Neo4j). Experience in evaluating LLM models. A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics. Background in health technology and/or medical content workflows is preferred. Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark. Experience with large-scale data processing systems, e.g., Spark. Experience with statistical analysis, machine learning theory and natural language processing. Elsevier is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services. It is one of the largest publishers of academic journals and scholarly literature in the world. Elsevier operates in various domains, including science, technology, medicine, social sciences, and more. They publish a vast number of peer-reviewed journals covering a wide range of disciplines. These journals act as platforms for researchers and academics to share their findings and contribute to the advancement of knowledge in their respective fields. U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New Jersey, the base pay range is $112,574 - $179,826. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.

The expected hiring range for this position is: $99,500.00-$130,900.00. Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such the scope and responsibilities of the position, qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. This position can potentially offer relocation. About the Role: The Controls Department in the Accelerator Directorate at Fermilab has an immediate need for a Kubernetes Engineer to develop requirements, perform R&D, and participate in design efforts for control system infrastructure concentrating on Kubernetes Cloud Native technologies. This senior computing services specialist will work within the Accelerator Control Department to build out and maintain the Kubernetes computing platform, integrate storage solutions, modernize the control system infrastructure, as well as assist in migrating legacy services and applications to the Kubernetes environment. This person will work within the team to ensure the smooth integration of the PIP-II control system with the rest of the complex and ensure reliable operation for LBNF/DUNE. What your day-to-day as a Kubernetes Engineer will look like: Perform R&D activities on Cloud Native technologies in support of the goal for reliable operations for LBNF/DUNE. Plan for the evolution of Kubernetes systems and services, including security, cybersecurity, capacity, and logistical planning. Gather, interpret, and implement user requirements and specify Kubernetes solutions to satisfy requirements for complex and challenging control system infrastructure needs. Mentor others on the architecture of the infrastructure, design principles, and best practices. Troubleshoot complex, unique, cutting-edge problems or issues related to the infrastructure where AI cannot help. Act as a technical subject matter expert and interface with and provide consultation to supporting services, as well as to service and system users. Operate on-premise Kubernetes and other on-premise Cloud Native products in support of the LBNF/DUNE scientific program. Apply multi-disciplinary knowledge and skills to the design, development, implementation, operation, and documentation of very complex, state-of-the-art information, computing, networking, and storage systems and services to support Accelerator Directorate objectives. Ensure integration of these systems with legacy systems. Essential Competencies and Attributes for Success: Bachelor of Computer Science or a related field with 5+ years of experience designing, building, and maintaining complex infrastructure systems. Applicable Knowledge, Skills and Abilities Required: Demonstrated experience with system administration of Linux environments is required. Experience with installing, configuring, and administering on-premise air-gapped Kubernetes, is required. Experience with networking and software defined networking is required. Experience with system configuration management (e.g., Puppet, Chef, Ansible) is required. Experience with version control management (e.g., git, GitHub, GitLab) is required. Experience implementing authorization tools and services (e.g., KeyCloak) is required. Ability to communicate effectively in English both verbally and in writing is required. Experience with GitOps methodologies is desired. Experience developing, managing, and using CI/CD pipelines (e.g., GitHub Runners, Jenkins) is required. Experience with cloud technologies is desired. Programming experience (e.g., Python, Bash scripting, Go) is desired. Experience with Ceph or other distributed storage is desired. Must be self-motivated, have good social skills and time management skills to work with diverse groups of managers, engineers, and scientists. Experience working in a national laboratory environment is desirable. Experience with accelerator control systems is a plus. Work Arrangement: Onsite: This is an onsite role, and the candidate must be able to work from our Batavia office. Benefits/Perks: Fermilab offers a competitive and comprehensive benefits program, including: Medical, Dental, Vision and Flexible Spending Account Paid time-off Life insurance Short and Long-term disability insurance Retirement benefits Onsite day care Why Fermilab: Fermilab is America's premier laboratory for particle physics and accelerator research, funded by the U.S. Department of Energy. We support discovery science experiments in Illinois and locations around the world, including deep underground mines in South Dakota and Canada, mountaintops in Arizona and Chile, CERN in Europe and the South Pole. Pre-Employment Screening: Drug-Free Workplace & Pre-Employment Screening Fermilab is dedicated to fostering a safe, productive and drug-free environment. An offer of employment is contingent upon the successful completion of a background check and drug screening. HSPD-12 In accordance with Homeland Security Presidential Directive 12 (HSPD-12) new employees are required to obtain and maintain a HSPD-12 Personal Identity Verification (PIV) Credential. To obtain this credential, new employees must successfully complete and pass a federal background check investigation. This investigation includes a declaration of illegal drug activities, including use, supply, possession, or manufacture. This includes marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment. Foreign Government Sponsored Activities Fermilab employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. Such individuals will be asked to disclose any participation for review by Fermilab's Office of General Counsel. REAL-ID Requirement for access to Fermilab Campus Fermilab requires all members of the public to produce a REAL-ID, or equivalent, to access the Fermilab Campus for interviews or career events. A list of acceptable forms of ID can be found here: If a candidate is selected for an interview but does not possess any of the equivalent documents, we may schedule a virtual interview. Equal Opportunity Statement Fermilab is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, age, national origin, disability, veteran status, genetic information, and other legally protected categories.

Job Description Job Description Position Summary The Senior Manager, Data Integrity & Governance is responsible for leading and managing the Sharp Sterile Manufacturing site data integrity initiatives, with a focus on ensuring the accuracy, completeness, consistency, and reliability of GXP data across computerized and paper-based systems. The role will oversee the site's development, implementation, and monitoring of data integrity processes, policies, and tools that align with regulatory requirements, and enable adherence to ALCOA+ principles. The site Data Integrity Lead will work closely with the site functions including; IT, Manufacturing, Quality and Engineering to enable Data Integrity compliance using a Quality risk management approach. The site Data Integrity Lead will collaborate with the Director, Data Integrity at the Allentown site to ensure alignment with corporate initiatives and the consistent implementation of Data Integrity standards, governance practices, risk assessment methodologies, training programs, and continuous improvement activities across the organization. The primary responsibilities of this role include site training on the requirements of ALCOA+, ensuring processes and procedures are in place to implement ALCOA+ principles in paper and computerized systems, ensuring that computerized system access controls, audit trail reviews and back-up and restore functions are appropriately implemented and meet cGMP requirements. The site Data Integrity Lead will also have responsibility for implementing and maintaining risk-based methodologies for the assessment and management of data integrity risks. The site Data Integrity Lead will drive a Data Integrity Management program across the Lee, MA manufacturing facility. This site-based role requires a strong leader with excellent communication skills and who is capable of prioritizing and managing multiple projects effectively. The successful candidate will be responsible for ensuring cGMP compliance as it pertains to Data Integrity Management across site operations and for implementing applicable corporate standards locally. Duties and Responsibilities Lead and maintain the site Data Integrity Management Program, including defining site objectives and scope, implementing corporate data integrity requirements, development and refinement of site procedures, implementing processes and metrics to monitor the effectiveness of the site Data Integrity program. Serve as the site Data Integrity subject matter expert (SME) during regulatory inspections and client audits, train/coach personnel on ALCOA+ principles and associated regulations and guidance documents. (e.g. GAMP5, PIC/S, 21 CFR Part 11, EudraLex Annex 11, FDA's Guidance for Industry, "Data Integrity and Compliance with Drug CGMP: Questions and Answers" (Final, 2018 . Report to the Site Quality Head and serve on the site Quality Leadership team and governance forums. Provide leadership and guidance to site functional representatives and system or process owners supporting Data Integrity objectives. Ensure site personnel understand and implement risk-based methodologies are understood and implemented as they pertain to data integrity management, especially when assessing legacy computerized systems, when validating new computerized systems and when evaluating proposed changes to existing computerized systems. Collaborate with the applicable corporate and site Data Governance, Quality, and Information Technology functions to integrate data integrity into the overall data governance framework, with particular emphasis on computerized systems and adherence to ALCOA+ principles. Collaborate cross-site to ensure that roles and responsibilities are clear regarding data management and stewardship of data integrity management. Provide guidance on the process to evaluate data integrity compliance through audits of Sharp and its suppliers. Lead or support site Data Integrity risk assessments, investigations, root cause analyses, corrective and preventive actions, and remediation plans. Ensure Data Integrity considerations are incorporated into computerized system validation, change control, incident management, periodic review, and system retirement activities. Review and trend site Data Integrity metrics, communicate program status and risks to site leadership, and drive continuous improvement and inspection readiness. Monitor relevant regulatory and industry expectations, assess site impact, and coordinate implementation of required site actions. Regulatory Responsibilities Conduct business in a responsible manner that complies with all state, OSHA, and HIPAA regulations Maintain a detailed and comprehensive understanding of FDA, EU, and other regulatory agency requirements as it pertains to data integrity. Supervisory Responsibilities This position has no direct reporting line responsibility; however, it will provide functional leadership and oversight to Data Integrity representatives and subject matter experts embedded within site operational units to support the execution of the Data Integrity Program. Experience Prefer a minimum of 5 years of experience in data management, data governance frameworks, and data quality tools, with a focus on computerized systems and adherence to ALCOA+ principles. Also prefer a minimum of at least 1.5 years in a leadership role within a pharmaceutical operation. Expertise in the application of 21 CFR Part 11, EudraLex Annex 11 and GAMP standards for data integrity and validation of automated systems is required. Proven experience of managing data integrity initiatives, particularly in relation to computerized systems, within a pharmaceutical organization. Experience collaborating cross functionally on investigations, CAPAs, risk assessments, and remediation programs associated with Data Integrity events or observations. Demonstrated history of influencing, motivating and effecting change with cross functional teams. Ability to independently determine and develop approaches to address simple to complex issues. Knowledge of and skill in using computer software and hardware applications. Excellent verbal and written communication/documentation skills with a demonstrated ability to clearly present technical topics to a non technical audience. Ability to influence and engage stakeholders at all levels. Excellent project management skills with the ability to manage multiple initiatives simultaneously. Strong analytical skills with the ability to interpret complex data sets from computerized systems and provide actionable insights. Experience of working in a sterile pharmaceutical manufacturing environment preferred. Education BS or higher degree in an IT, engineering, scientific discipline or other related field. A master's degree is a plus. Knowledge, Skills & Abilities Skilled in the use of Microsoft office applications (Word, Excel, PowerPoint) and Adobe Acrobat High attention to detail Good writing, public speaking and presentation skills Must be able to travel approximately 10% of the time Physical Requirements Ability to sit for prolonged periods of time Ability to stand for prolong periods of time as required Able to lift up to 10lbs