engineering research manager

Mirage Electronics (pvt.) Ltd.

<p>Sigma Refrigeration Limited, seeking a dynamic and experienced <b>Engineering Manager</b> to lead Research &amp; Development, Planning, and Product Design functions.</p><p><b>Key Responsibilities:</b></p><ul><li>Lead and manage <b>Research &amp; Development (R&amp;D)</b> activities for new and existing home appliance products.</li><li>Develop new product designs, improvements, and cost-optimization strategies.</li><li>Oversee <b>production planning and coordination</b> to ensure efficient manufacturing operations.</li><li>Collaborate with cross-functional teams including production, quality assurance, procurement, and sales.</li><li>Conduct feasibility studies for new product development and localization projects.</li><li>Ensure compliance with engineering standards, safety regulations, and quality benchmarks.</li><li>Drive continuous improvement initiatives in processes, design, and manufacturing efficiency.</li><li>Supervise prototype development, product testing, and validation.</li><li>Monitor technical performance and resolve engineering-related issues.</li></ul><p><b>Qualification &amp; Experience:</b></p><ul><li><b>BS / BE in Mechanical</b>.</li><li>Minimum <b>5&ndash;8 years of relevant experience</b> in home appliances manufacturing.</li><li>Strong knowledge of production planning, product design, and R&amp;D processes.</li><li>Experience in assembly line management and technical troubleshooting.</li><li>Good leadership, analytical, and project management skills.</li><li>Proficiency in CAD software and ERP systems.</li></ul><p><b>We Offer:</b></p><ul><li>Market Competitive Salary</li><li>Growth-Oriented Work Environment</li></ul><p><b>Job Location</b>: Sundar Industrial Estate Raiwind Road, Lahore, Pakistan</p><p>Job Type: Full-time</p><p>Education:</p><ul><li>Bachelor's (Preferred)</li></ul><p>Experience:</p><ul><li>Home Appliance Manufacturing Industry: 4 years (Required)</li></ul><p>Work Location: In person</p>

Engineering Manager (R&D & Planning)

Eaton

<div><div><div><div><h2 class="jobSectionHeader"><b>What you&rsquo;ll do:</b></h2>
</div><div><div>
Job Responsibilities<br>
The Manager will be responsible for:<br>
<ul><li>Lead and manage a team of Engineers to deploy and monitor machine learning models in production.</li><li>Working with data engineers for designing data engineering pipelines and performs robust ETL processes to ensure reliable, high‑quality data for analytics and ML workloads.</li><li>Collaborate with cross-functional teams, including data science, engineering, and operations, to understand business requirements and translate them into scalable ML solutions.</li><li>Architect and implement end-to-end machine learning pipelines for model training, testing, deployment, and monitoring.</li><li>Establish best practices and standards for model versioning, deployment, and monitoring to ensure reliability, scalability, and performance.</li><li>Implement automated processes for model training, hyperparameter tuning, and model evaluation using tools such as Weight and Biases, MLflow, Kubeflow, or similar.</li><li>Design and implement infrastructure for scalable and efficient model serving and inference, leveraging technologies such as Kubernetes, Docker, and serverless computing.</li><li>Develop and maintain monitoring and alerting systems to detect model drift, performance degradation, and other issues in production.</li><li>Provide technical leadership and mentorship to team members, fostering their professional growth and development.</li><li>Stay current with emerging technologies and industry trends in machine learning engineering, and evaluate their potential impact on our processes and infrastructure.</li><li>Collaborate with product management to define requirements and priorities for machine learning model deployments and validation, ensuring alignment with business goals and objectives.</li><li>Implement monitoring and logging solutions to track model performance metrics, resource utilization, and system health, enabling proactive issue detection and resolution.</li><li>Lead efforts to optimize resource utilization and cost-effectiveness of machine learning infrastructure, including compute resources, storage, and data transfer.</li><li>Stay abreast of advancements in machine learning technologies, evaluating their applicability and potential impact on our AI Operations strategy and roadmap.</li><li>Foster a culture of innovation, collaboration, and continuous improvement within the AI Operations team, encouraging experimentation and learning from failures.</li></ul></div></div></div><div><div><h2 class="jobSectionHeader"><b>
Qualifications:</b></h2>
</div><div><ul><li>B.tech / M Tech in Computer Science, Electronics or related fields</li><li>
8 Years +</li></ul></div></div><div><div><h2 class="jobSectionHeader"><b>
Skills:</b></h2></div><p></p><div><br>
<ul><li>
Machine Learning, Software Development</li><li>
Research and development, Technology strategy, Global Project Management, Team Management, Mentoring, Risk Management.</li><li>
Desired Skills :<br>
<ul><li>Masters or Bachelor's degree in Computer Science, Engineering, or related field</li><li>8+ years of experience in software engineering, data engineering, or related roles, with at least 2 years in a managerial or leadership role.</li><li>Experience in Designs and maintains scalable data engineering pipelines and performs robust ETL processes to ensure reliable, high‑quality data for analytics and ML workloads</li><li>Previous experience in a leadership or management role, with a track record of successfully leading technical teams and delivering high-impact projects.</li><li>Experience with version control systems (e.g., Git) and collaboration tools (e.g., GitHub, GitLab) for managing code repositories and facilitating team collaboration.</li><li>Familiarity with infrastructure as code (IaC) tools such as Terraform or CloudFormation for provisioning and managing cloud resources.</li><li>Knowledge of software development methodologies (e.g., Agile, DevOps) and best practices for building scalable and reliable software systems.</li><li>Ability to effectively communicate technical concepts and solutions to non-technical stakeholders, including executives, product managers, and business users.</li><li>Strong proficiency in Python, JAVA and related IDEs</li><li>Awareness of machine learning concepts, algorithms, and frameworks (e.g. TensorFlow, PyTorch, sci-kit-learn).</li><li>Experience with cloud platforms and services (e.g., Azure, AWS, GCP) for building and deploying machine learning applications.</li><li>Proficiency in containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes).</li><li>Hands-on experience with MLOps tools and platforms such as Weight and Biase, MLflow, Kubeflow, TFX, or similar.</li><li>Experience in DevOps and DevSecOps tools and practices</li><li>Strong problem-solving skills and ability to troubleshoot complex issues in production environments.</li><li>Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams.</li></ul></li></ul></div></div></div></div>

Engineering Manager - Machine Learning

Innodata

<div><p><b>Who we are:</b></p><p>
Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2,000 customers and operations in 13 cities around the world, we are the AI technology solutions provider-of-choice to 4 out of 5 of the world&rsquo;s biggest technology companies, as well as leading companies across financial services, insurance, technology, law, and medicine.</p><p>
By combining advanced machine learning and artificial intelligence (ML/AI) technologies, a global workforce of subject matter experts, and a high-security infrastructure, we&rsquo;re helping usher in the promise of clean and optimized digital data to all industries. Innodata offers a powerful combination of both digital data solutions and easy-to-use, high-quality platforms.</p><p>
Our global workforce includes over 3,000 employees in the United States, Canada, United Kingdom, the Philippines, India, Sri Lanka, Israel and Germany. We&rsquo;re poised for a period of explosive growth over the next few years.</p><p></p><p><b>
Position Summary:</b></p><p>
Innodata is expanding its team of technical experts in LLM training, post-training, and evaluation systems. As an AI/ML Research Engineer, LLM Training &amp; Evaluation, you will build and optimize the technical foundations that power model improvement for foundation model builders and leading labs.</p><p>
This role is ideal for someone who has hands-on experience fine-tuning and evaluating large language models (and ideally multimodal models), and who can bridge research and engineering in real-world customer environments. You will work closely with Language Data Scientists, Applied Research Scientists, data engineers, and client technical stakeholders to design and implement robust training/evaluation pipelines using both human-in-the-loop and AI-augmented methods.</p><p>
The ideal candidate brings a strong computer science / machine learning engineering background, experience with modern LLM post-training workflows, and the ability to engage credibly with technical counterparts at leading AI organizations.</p><p></p><p><b>
Who We&rsquo;re Looking For:
</b></p><p>You have at least 2-3 years of relevant experience in machine learning engineering, applied ML systems, or research engineering, with substantial hands-on work in LLMs and multimodal foundation models. You have built, adapted, or optimized model training and evaluation pipelines, and you understand the practical realities of experimentation at scale: reproducibility, debugging, metrics quality, and iteration speed.</p><p>
You are comfortable operating in ambiguous, high-complexity environments and can move from problem framing to implementation. You can collaborate effectively with both researchers and engineers, and you are credible in technical conversations with sophisticated customer stakeholders (e.g., AI researchers, ML engineers, technical product leads).</p><p>
You bring a builder mindset and strong engineering judgment, while also understanding that evaluation quality and data quality are central to model improvement. You are excited to partner with human evaluation experts and language data scientists to create integrated post-training and evaluation systems.</p><p></p><p><b>
Tell Me More:</b>
</p><p>As an AI/ML Research Engineer, LLM Training &amp; Evaluation, you will design and implement the pipelines and tooling that connect data, evaluation, and post-training. You will help customers and internal teams move from evaluation findings to measurable model improvements.</p><p>
Your work may include building fine-tuning workflows (e.g., supervised fine-tuning and preference-based optimization), integrating evaluation harnesses into model development loops, improving experiment reliability and throughput, and supporting advanced evaluation scenarios such as long-context, cross-modal, and dynamic multi-turn interactions.</p><p>
You will also contribute to Innodata&rsquo;s internal R&amp;D efforts, including benchmark datasets, evaluation frameworks, and reusable infrastructure for model assessment and post-training experimentation.</p><p></p><p><b>
Responsibilities:</b></p><ul><li>
Lead or co-lead technically complex ML engineering projects from initial customer discussions through implementation and delivery</li><li>
Design, build, and improve LLM training and post-training pipelines, including data ingestion, preprocessing, fine-tuning, evaluation, and experiment tracking</li><li>
Implement and optimize evaluation systems for LLMs and multimodal models, including offline benchmarks and task-specific test harnesses</li><li>
Integrate human-in-the-loop and AI-augmented evaluation signals into model development workflows</li><li>
Build robust infrastructure and tooling for reproducible experimentation, metrics logging, and regression monitoring</li><li>
Diagnose model behavior and pipeline failures, including data issues, training instability, metric inconsistencies, and evaluation drift</li><li>
Collaborate with Language Data Scientists and Applied Research Scientists to translate evaluation frameworks into executable systems</li><li>
Work closely with customer technical stakeholders to understand goals, constraints, and success criteria; propose and implement technically sound solutions</li><li>
Contribute to internal research and platform development, including benchmark frameworks, evaluation tooling, and post-training workflow improvements</li><li>
Contribute to best practices and standards for LLM training, evaluation, and quality assurance across projects</li><li>
Mentor junior engineers and contribute to technical design reviews, documentation, and engineering rigor across the team</li></ul><ul><li>
BS/MS/PhD in Computer Science, Machine Learning, AI, Applied Mathematics, or a related quantitative technical field (MS/PhD preferred)</li><li>
2-3 years of relevant industry or research engineering experience in ML/AI systems</li><li>
Hands-on experience with LLM training / fine-tuning / post-training, including at least one of:<ul><li>
supervised fine-tuning (SFT)</li><li>
preference optimization (e.g., DPO or related methods)</li><li>
RLHF / RLAIF-style workflows</li><li>
task- or domain-adaptation of foundation models</li></ul></li><li>
Strong programming skills in Python and experience building production-quality ML code</li><li>
Experience with modern ML frameworks (e.g., PyTorch, JAX, TensorFlow) and model libraries/tooling (e.g., Hugging Face ecosystem, vLLM, distributed training stacks)</li><li>
Experience designing and implementing evaluation pipelines for LLM/ML systems, including metrics computation, dataset handling, and experiment comparisons</li><li>
Strong understanding of data pipelines and ML systems engineering, including reproducibility, observability, and debugging</li><li>
Experience with large-scale distributed ML systems and performance optimization for training/evaluation workloads (GPU/accelerator environments preferred)</li><li>
Experience with large-scale data processing and workflow orchestration in support of model training/evaluation</li><li>
Ability to collaborate directly with technical stakeholders including research scientists, ML engineers, data engineers, and customer technical leads</li><li>
Strong written and verbal communication skills, including the ability to explain complex technical tradeoffs to both technical and non-technical audiences</li></ul><p></p><p><b>
Technical Skills</b></p><p>
ML / LLM Engineering</p><ul><li>
Experience training, fine-tuning, and evaluating transformer-based models</li><li>
Understanding of post-training workflows and model iteration loops</li><li>
Familiarity with inference-time considerations (latency, throughput, memory/performance tradeoffs) where relevant to evaluation or deployment</li></ul><p>
Evaluation &amp; Experimentation</p><ul><li>
Experience implementing automated evaluation pipelines and test harnesses</li><li>
Experience with experiment tracking, versioning, and reproducibility practices</li><li>
Ability to assess metric quality and ensure consistency across model comparisons</li></ul><p>
Software / Data Engineering</p><ul><li>
Proficiency in Python and strong software engineering fundamentals</li><li>
Experience with data processing pipelines, storage formats, and scalable dataset workflows</li><li>
Familiarity with CI/CD, testing, and engineering quality practices for ML systems</li></ul><p></p><p><b>
Preferred Skills</b></p><ul><li>
Experience with multimodal model training/evaluation (text + image/audio/video)</li><li>
Experience with long-context evaluation and/or model adaptation for long-context tasks</li><li>
Experience with agentic or multi-turn evaluation harnesses, tool-use simulation, or interactive environment testing</li><li>
Experience working in customer-facing technical consulting, solutions engineering, or applied research delivery</li><li>
Familiarity with LLM safety, alignment, robustness, or red-teaming evaluation approaches</li><li>
Contributions to open-source ML/LLM tooling or published technical work in relevant areas</li></ul><p></p><p><b>
How this role partners with the team</b></p><p>
This role works closely with:</p><ul><li>
Language Data Scientists, who lead human evaluation design, language/data process excellence, and annotation/synthetic workflows</li><li>
Applied Research Scientists, who lead evaluation methodology, benchmarking research, and experimental design</li><li>
Data Engineers / Platform Teams, who support scalable data and infrastructure foundations</li><li>
Customer Technical Stakeholders, who rely on Innodata for expert guidance and implementation support in advanced GenAI development</li></ul><p></p><p><i>
Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission&rsquo;s guide at </i>https://consumer.ftc.gov/articles/job-scams.</p><p><i>
If you believe you&rsquo;ve been targeted by a recruitment scam, please report it to Innodata at </i>verifyjoboffer@innodata.com<i> and consider reporting it to the FTC at </i>ReportFraud.ftc.gov<i>.</i></p><p></p><p>
#LI-NS1</p></div><p></p>

AI/ML Research Engineer, LLM Post-Training & Evaluation

Google

<div><h3 class="jobSectionHeader"><b>Minimum qualifications:</b></h3><ul>
<li>Bachelor's degree or equivalent practical experience.</li>
<li>8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).</li>
<li>3 years of experience in a technical leadership role; overseeing projects, with 2 years of experience in a people management, supervision/team leadership role.</li></ul><br>
<h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul>
<li>Experience designing, developing, and deploying large-scale AI/ML systems in a cloud environment.<br>
</li>
<li>Experience with Google Cloud Platform (GCP).</li>
<li>Understanding of a wide range of machine learning algorithms, statistical modeling techniques, and data analysis methodologies relevant to HR data and issues.</li>
<li>Excellent technical leadership, communication, and people management skills, with the ability to influence and collaborate effectively with both technical and non-technical audiences.</li>
</ul><div><h2 class="jobSectionHeader"><b>About the job</b></h2><p>
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started - and as a manager, you guide the way.<br>
<br>
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.</p><br>
<p>
In this role, you will join our Human Resources Engineering (HRE) team in Hyderabad. You will be a technical manager, driving the design, development, and deployment of sophisticated AI-powered solutions that significantly impact Google's employees. You will have an opportunity to work on Google-scale infrastructure, mentor a talented team of Engineers, collaborate with cross-functional partners, and contribute strategically to the future of HR at Google through innovative AI applications. You will be responsible for translating complex business issues and strategic objectives into scalable, and efficient AI/ML systems.</p><p>
At Corp Eng, we build world-leading business solutions that scale a more helpful Google for everyone. As Google&rsquo;s IT organization, we provide end-to-end solutions for organizations across Google. We deliver the right tools, platforms, and experiences for all Googlers as they create more helpful products and services for everyone. In the simplest terms, we are Google for Googlers.</p></div><div><h2 class="jobSectionHeader"><b>
Responsibilities</b></h2><ul>
<li>Lead and manage a team of AI Software Engineers, fostering a collaborative and high-performing environment. This includes hiring, mentoring, performance management, and career development.</li>
<li>Drive the design, development, and deployment of scalable and reliable AI/ML systems and infrastructure relevant to HR applications (e.g., talent acquisition, performance management, employee engagement, workforce planning).</li>
<li>Ensure the successful deployment, monitoring, and maintenance of AI/ML models in Google's production environments, advocating Machine Learning Operations (MLOps) best practices within the team.</li>
<li>Drive technical excellence within the team, promoting high code quality, thorough testing, and adherence to Google's engineering standards.</li>
<li>Identify and address technical issues and risks, making strategic decisions and trade-offs to ensure timely and high-quality delivery.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Engineering Manager, AI Software Engineering, Human Resources Engineering

Penspen

<div><div><div><div><div><div><div><p><b>Responsibilities:
</b></p><ul><li>Direct and manage the onboarding, training, and professional development programs for engineering graduates, ensuring alignment with company objectives, technical and project requirements.</li>
<li>Coordinate and oversee the day-to-day activities of multi-disciplinary engineering graduates, with a focus on their professional development and continuous growth.</li>
<li>Develop and implement detailed plans for ensuring that engineering graduates contribute effectively to project objectives while gaining exposure to various technical areas.</li>
<li>Monitor the quality of engineering work performed by graduate engineers, ensuring technical standards and project requirements are met within agreed timelines.</li>
<li>Foster an inclusive and supportive work environment by leading, mentoring, coaching, and motivating engineering graduates to achieve their full potential.</li>
<li>Work closely with the Engineering Performance Manager, Technical Discipline Authorities, and Project Managers to integrate graduate engineers into larger engineering teams and ensure their technical skills are continuously developed.</li>
<li>Consult with clients (internal and external wherever required) to ensure a clear understanding of project requirements and deliverables, ensuring graduate engineers are prepared to support client-facing needs when required.</li>
<li>Collaborate with HR and senior management to recommend strategies for recruiting, training, and retaining engineering graduates, ensuring alignment with strategic business goals and targets.</li>
<li>Regularly assess the progress and development of engineering graduates, providing feedback and adjusting development plans as necessary, and documenting performance in the Performance at Penspen system.</li>
<li>Stay up to date with industry trends and best practices in engineering education and development to improve training processes.</li>
<li>Development, implementation and monitoring of engineering graduate training and development processes/procedures.</li></ul></div></div></div></div></div></div></div>

Engineering Graduate Development Manager

<div><p><b>Line of Service
</b></p>Advisory
<p></p><p><b>Industry/Sector
</b></p>Technology
<p></p><p><b>Specialism
</b></p>Advisory - Other
<p></p><p><b>Management Level
</b></p>Manager
<p></p><p><b>Job Description &amp; Summary
</b></p>The PwC ETIC is seeking an experienced Applied AI Solution Engineer/Solution Architect to join our dynamic team. In this role, you will be responsible for providing technical consulting services to our clients, envisioning, building, deploying, and operationalizing end-to-end machine learning (ML) and AI pipelines. You will play a key role in designing technical architectures, selecting appropriate tools and technologies, and ensuring seamless integration of new solutions within existing ecosystems.
<p></p><div><div><p>Key Responsibilities
</p></div><div><ul><li><p>Design and develop robust technical architectures for ML and AI solutions.
</p></li></ul></div><div><ul><li><p>Choose and implement optimal tools and technologies for each project.
</p></li></ul></div><div><ul><li><p>Develop and operationalize AI models and algorithms, ensuring scalability and reliability.
</p></li></ul></div><div><ul><li><p>Plan integration strategies for new solutions into existing client ecosystems.
</p></li></ul></div><div><ul><li><p>Translate stakeholder and business analyst suggestions into actionable technical plans, elaborating project vision.
</p></li></ul></div><div><ul><li><p>Collaborate closely with security and risk leaders to identify, address, and mitigate potential risks.
</p></li></ul></div><div><ul><li><p>Work alongside data scientists and AI professionals to support digital transformation initiatives.
</p></li></ul></div><div><ul><li><p>Stay up to date with emerging technologies and solutions to continuously add value for clients.
</p></li></ul></div><div><ul><li><p>Provide expert guidance to clients on business requirements and industry best practices.
</p></li></ul></div><div><ul><li><p>Deliver presentations and communicate complex technical concepts clearly to diverse audiences.
</p></li></ul></div><div><p>Requirements
</p></div><div><ul><li><p>Bachelor&rsquo;s degree in Computer Science or a related field (Master&rsquo;s degree preferred in Computer Science, Data Science, or AI-related discipline).
</p></li></ul></div><div><ul><li><p>Minimum 8+ years of experience in Applied AI Solution Architecture.
</p></li></ul></div><div><ul><li><p>Proficiency in machine learning frameworks such as TensorFlow, Keras, and PyTorch.
</p></li></ul></div><div><ul><li><p>Expertise in programming languages like Python, and C # .
</p></li></ul></div><div><ul><li><p>Familiarity with cloud platforms such as A zure (primary) , A WS , and Google Cloud.
</p></li></ul></div></div><div><div><ul><li><p>Experience with big data technologies (e.g., Hadoop, Spark) and data warehousing/ETL tools.
</p></li></ul></div><div><ul><li><p>Strong problem-solving and communication skills.
</p></li></ul></div><div><ul><li><p>Ability to work independently and as part of a collaborative team.
</p></li></ul></div><div><ul><li><p>Proven track record of implementing machine learning solutions and statistical analysis.
</p></li></ul></div><div><ul><li><p>Demonstrated ability to handle customer queries and provide timely solutions.
</p></li></ul></div><div><p>Preferred Qualifications
</p></div><div><ul><li><p>Master&rsquo;s degree in relevant field.
</p></li></ul></div><div><ul><li><p>Experience in development using multiple programming languages.
</p></li></ul></div><div><ul><li><p>Knowledge of practical machine learning applications and a range of related approaches.
</p></li></ul></div><div><p>Core Competencies
</p></div><div><ul><li><p>Whole Leadership: Lead yourself and others to create a positive impact responsibly, authentically, and passionately.
</p></li></ul></div><div><ul><li><p>Global Acumen: Collaborate with a mindset that embraces diverse perspectives and transcends boundaries.
</p></li></ul></div><div><ul><li><p>Technical and Digital: Focus on rapidly evolving technologies and their application in digital transformation.
</p></li></ul></div><div><ul><li><p>Business Acumen: Apply business knowledge and innovation to deliver distinctive value for clients and PwC.
</p></li></ul></div><div><ul><li><p>Relationships: Build genuine and meaningful high-value relationships.
</p></li></ul></div><div><p>Required Skills
</p></div><div><ul><li><p>Active Listening
</p></li></ul></div><div><ul><li><p>Analytical Thinking
</p></li></ul></div><div><ul><li><p>Business Analysis &amp; Strategy
</p></li></ul></div><div><ul><li><p>Business Process Consulting &amp; Improvement
</p></li></ul></div></div><div><div><ul><li><p>Business Transformation
</p></li></ul></div><div><ul><li><p>Coaching and Feedback
</p></li></ul></div><div><ul><li><p>Communication
</p></li></ul></div><div><ul><li><p>Competitive Analysis &amp; Advantage
</p></li></ul></div><div><ul><li><p>Conducting Research
</p></li></ul></div><div><ul><li><p>Consumer Behavior
</p></li></ul></div><div><ul><li><p>Creativity
</p></li></ul></div><div><ul><li><p>Customer Experience (CX) Strategy
</p></li></ul></div><div><ul><li><p>Customer Insight &amp; Strategy
</p></li></ul></div><div><ul><li><p>Data Analytics
</p></li></ul></div><div><ul><li><p>Embracing Change
</p></li></ul></div><div><ul><li><p>Emotional Regulation
</p></li></ul></div><div><ul><li><p>Empathy
</p></li></ul></div><div><ul><li><p>Go-to-Market Strategies
</p></li></ul></div><div><p>Optional Skills
</p></div><div><ul><li><p>Additional technical certifications
</p></li></ul></div><div><ul><li><p>Knowledge of emerging AI trends
</p></li></ul></div><div><p>If you are passionate about leveraging advanced analytics and AI to deliver innovative solutions and exceed client expectations, we encourage you to apply and become a valued member of our team.
</p></div></div><p></p><p><b>Education </b><i>(if blank, degree and/or field of study not specified)
</i></p>Degrees/Field of Study required:
<p></p>Degrees/Field of Study preferred:
<p></p><p><b>Certifications </b><i>(if blank, certifications not specified)
</i></p><p></p><p><b>Required Skills
</b></p><p></p><p><b>Optional Skills
</b></p>Accepting Feedback, Accepting Feedback, Active Listening, Analytical Thinking, Business Analysis, Business Opportunities, Business Process Consulting, Business Process Improvement, Business Strategy, Business Transformation, Coaching and Feedback, Communication, Competitive Advantage, Competitive Analysis, Conducting Research, Consumer Behavior, Creativity, Customer Experience (CX) Strategy, Customer Insight, Customer Strategy, Data Analytics, Embracing Change, Emotional Regulation, Empathy, Go-to-Market Strategies {+ 19 more}
<p></p><p><b>Desired Languages </b><i>(If blank, desired languages not specified)
</i></p><p></p><p><b>Travel Requirements
</b></p>0%
<p></p><p><b>Available for Work Visa Sponsorship?
</b></p>No
<p></p><p><b>Government Clearance Required?
</b></p>No
<p></p><p><b>Job Posting End Date</b></p></div><p></p>

ETIC, AI Engineer - Manager

KPMG

<div><p>Known for being a great place to work and build a career, KPMG provides audit, tax and advisory services for organizations in today's most important industries. Our growth is driven by delivering real results for our clients. It's also enabled by our culture, which encourages individual development, embraces an inclusive environment, rewards innovative excellence and supports our communities. With qualities like those, it's no wonder we're consistently ranked among the best companies to work for by Fortune Magazine, Consulting Magazine, Seramount, Fair360 and others. If you're as passionate about your future as we are, join our team.</p>
<p>KPMG is currently seeking a Quantum Researcher, Manager to join our Enterprise Solutions team.</p><h3 class="jobSectionHeader"><b>
Responsibilities:</b></h3><ul><li>
Conduct advanced research on quantum algorithms, error correction, and hybrid quantum-classical systems, with a focus on near-term applications in optimization, simulation, and machine learning</li><li>
Develop and benchmark quantum solutions using gate-based platforms (IBM Quantum, IonQ, Azure Quantum) and quantum annealing systems (D-Wave) as appropriate to client requirements; design and implement quantum machine learning (QML) and quantum neural network (QNN) approaches for classification, regression, and generative modeling use cases</li><li>
Formulate client problems using quantum optimization techniques including variational algorithms, adiabatic methods, and hybrid classical-quantum architectures</li><li>
Evaluate quantum hardware and software vendors to support client technology selection and roadmap decisions; collaborate on interdisciplinary projects, integrating quantum technologies with classical AI/ML to enhance optimization and simulation capabilities</li><li>
Publish insights, whitepapers, and present findings at industry forums, contributing to KPMG's thought leadership in quantum computing; partner with universities, research institutes, and clients to prototype quantum solutions and evaluate their business impact</li><li>
Support business development through proposal contributions, capability demonstrations, and client workshops</li><li>
Act with integrity, professionalism, and personal responsibility to uphold KPMG's respectful and courteous work environment</li></ul><h3 class="jobSectionHeader"><b>
Qualifications:</b></h3><ul><li>
Minimum five years of recent experience in related fields (optimization, computational physics, operations research, machine learning) with demonstrated quantum competencymin a professional service environment is preferred; minimum three years of recent experience in quantum research or development</li><li>
PHD from an accredited college or university is preferred; minimum of a Master's degree in quantum computing, physics, computer science, mathematics, or a related field required is required</li><li>
Experience with quantum machine learning techniques including quantum kernel methods, parameterized quantum circuits, and quantum neural network architectures</li><li>
Strong publication record or demonstrated contributions to quantum software, open-source projects, or commercial quantum applications, IBM Quantum Developer Certification or equivalent vendor credentials highly preferred</li><li>
Hands-on experience with quantum programming frameworks (Qiskit, Cirq, PennyLane, Ocean SDK) and simulation tools; familiarity with NISQ device characteristics and limitations; proven track record applying quantum technologies to business problems such as combinatorial optimization, simulation, or machine learning acceleration; experience designing and running experiments on real quantum hardware, including error mitigation strategies</li><li>
Travel twenty to forty percent required client engagements, and industry collaborations</li><li>
Deep knowledge of quantum mechanics, linear algebra, and optimization theory</li><li>
Applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future. KPMG LLP will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa)</li></ul>
<div>KPMG LLP and its affiliates and subsidiaries (&ldquo;KPMG&rdquo;) complies with all local/state regulations regarding displaying salary ranges. If required, the ranges displayed below or via the URL below are specifically for those potential hires who will work in the location(s) listed. Any offered salary is determined based on relevant factors such as applicant's skills, job responsibilities, prior relevant experience, certain degrees and certifications and market considerations. In addition, KPMG is proud to offer a comprehensive, competitive benefits package, with options designed to help you make the best decisions for yourself, your family, and your lifestyle. Available benefits are based on eligibility. Our Total Rewards package includes a variety of medical and dental plans, vision coverage, disability and life insurance, 401(k) plans, and a robust suite of personal well-being benefits to support your mental health. Depending on job classification, standard work hours, and years of service, KPMG provides Personal Time Off per fiscal year. Additionally, each year KPMG publishes a calendar of holidays to be observed during the year and provides eligible employees two breaks each year where employees will not be required to use Personal Time Off; one is at year end and the other is around the July 4th holiday. Additional details about our benefits can be found towards the bottom of our KPMG US Careers site at Benefits &amp; How We Work.</div><div></div><div><br>
Follow this link to obtain salary ranges by city outside of CA:</div>
https://kpmg.com/us/en/how-we-work/pay-transparency.html/?id=K10MG4_9_26 California Salary Range: $127200 - $236200
<div><div>KPMG offers a comprehensive compensation and benefits package. KPMG is an equal opportunity employer. KPMG complies with all applicable federal, state and local laws regarding recruitment and hiring. All qualified applicants are considered for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, citizenship status, disability, protected veteran status, or any other category protected by applicable federal, state or local laws. The attached link contains further information regarding KPMG's compliance with federal, state and local recruitment and hiring laws. No phone calls or agencies please.</div><div></div><div><br>
KPMG recruits on a rolling basis. Candidates are considered as they apply, until the opportunity is filled. Candidates are encouraged to apply expeditiously to any role(s) for which they are qualified that is also of interest to them.</div><div></div><div><br>
Los Angeles County applicants: Material job duties for this position are listed above. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness, and safeguard business operations and company reputation. Pursuant to the California Fair Chance Act, Los Angeles County Fair Chance Ordinance for Employers, Fair Chance Initiative for Hiring Ordinance, and San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</div></div></div>

Quantum Researcher, Manager

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