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Edurech Technoogy

Job Title: AI / Machine Learning EngineerAt Edurech Technology, we are redefining education through intelligent, data-driven learning platforms. By leveraging artificial intelligence and machine learning, we build personalized, adaptive, and scalable solutions that enhance learning outcomes for students and educators worldwide. We are looking for a skilled AI / Machine Learning Engineer to help design, build, and deploy intelligent systems that power the future of education.Job SummaryWe are seeking a motivated AI / Machine Learning Engineer with 2&ndash;6 years of experience to join our on-site team in Tempe. The ideal candidate has strong experience in machine learning, deep learning, and model deployment, along with a passion for solving real-world problems using AI. You will work closely with data scientists, software engineers, and product teams to develop and productionize AI-driven features across our platforms.Key ResponsibilitiesModel Development<ul><li>Design, build, train, and optimize machine learning and deep learning models for educational use cases such as personalization, recommendation systems, content classification, and student performance prediction.</li></ul>Data Processing<ul><li>Clean, preprocess, and analyze structured and unstructured datasets.</li><li>Perform feature engineering to improve model performance.</li></ul>Deployment &amp; MLOps<ul><li>Deploy machine learning models into production environments.</li><li>Monitor model performance, data drift, and accuracy, and retrain models as needed.</li></ul>AI Research &amp; Innovation<ul><li>Stay current with the latest AI/ML research and technologies.</li><li>Experiment with new algorithms, architectures, and tools to improve system performance.</li></ul>Collaboration<ul><li>Work with cross-functional teams including product, backend, and data teams to integrate AI solutions into applications.</li><li>Translate business and product requirements into scalable AI solutions.</li></ul>Documentation &amp; Improvement<ul><li>Document model architectures, experiments, and deployment processes.</li><li>Continuously improve AI pipelines, workflows, and system reliability.</li></ul>Required Qualifications &amp; SkillsExperience<ul><li>2&ndash;6 years of professional experience in AI, machine learning, or related roles.</li></ul>Education<ul><li>Bachelor&rsquo;s degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, or a related quantitative field.</li></ul>Programming<ul><li>Strong proficiency in Python.</li><li>Experience with ML/DL frameworks such as TensorFlow, PyTorch, Keras, or Scikit-learn.</li></ul>Machine Learning Knowledge<ul><li>Solid understanding of supervised and unsupervised learning, deep learning, and evaluation metrics.</li><li>Experience with NLP, computer vision, or recommendation systems is a plus.</li></ul>Data &amp; Tools<ul><li>Experience working with SQL and large datasets.</li><li>Familiarity with data processing libraries such as Pandas, NumPy, and Spark.</li></ul>Communication<ul><li>Strong verbal and written communication skills with the ability to explain AI concepts to non-technical stakeholders.</li></ul>Preferred Qualifications<ul><li>Master&rsquo;s or Ph.D. in AI, Machine Learning, or a related field.</li><li>Experience with cloud platforms (AWS, Azure, or GCP) and cloud-based ML services.</li><li>Familiarity with MLOps tools (MLflow, Kubeflow, Airflow).</li><li>Experience with model versioning, CI/CD, and containerization (Docker, Kubernetes).</li><li>Prior experience in EdTech, SaaS, or large-scale AI systems.</li><li>Proven experience taking AI/ML models from research to production.</li></ul>Job TypeFull-timeBenefits<ul><li>401(k)</li><li>401(k) matching</li><li>Dental insurance</li><li>Employee assistance program</li><li>Flexible schedule</li><li>Health insurance</li><li>Life insurance</li><li>Paid time off</li><li>Professional development assistance</li><li>Relocation assistance</li><li>Tuition reimbursement</li><li>Vision insurance</li></ul>Work LocationIn personJob Type: Full-timePay: $101,358.61 - $122,066.28 per yearWork Location: In person

AI/ML Engineer

Uber

<div>About the Role
 
 
Have you ever ordered a car service on Uber, and when the ride arrives, wondered how it got to you so fast? Ever ordered food on UberEats and wondered where the driver was before receiving your order and how long it took to get to the restaurant or if your order was ready when the courier arrived? Ever wondered why your grocery delivery from Uber always has the best apple picked?
 
 
If so, Uber is for you. In our ML and Science division, we strive to make magic within Uber's marketplace. This requires judgment to make difficult trade-offs, blending algorithms with human resourcefulness, and the ability to build simplicity from complexity. When we get the balance right for everyone, Uber magic happens. We build systems to peer into the future to craft the most cost-efficient marketplace for matching supply and demand. We are passionate about using innovative economics, machine learning, and scalable distributed software that automates and optimizes every aspect of this intricate dance between participants of the marketplace.
 
 
We are involved in every stage of the product development cycle and use data to inform product decisions, build models to power our solutions, and also develop platform tools that are used across teams with a primary focus on Mobility and Delivery. We work with millions of earners across the globe to make this magic happen and want you to join us!
 
 
About the Team
 
 
Earners (drivers and couriers) are an integral part of Uber's multi-sided marketplace. They provide the time and the means to move people and things. Importantly, they enable the connection between the physical and digital world to make the movement happen at the push of a button for everyone, everywhere.
 
 
Within Uber, Earner plays a critical role in earners' journey as the team is responsible for earner onboarding, activation, early life cycle, and resurrection. This presents the teams with the opportunity to shape and tailor the product experience during earners' many firsts (i.e., first time interacting on the Uber platform, choosing the earning opportunity, going online, receiving incentive offers, completing a trip, or reading the earnings summary). These firsts can be daunting.
 
 
Therefore, making sure that the earner journey is great at every touch point is important to build trust with Earners, communicate Uber's value proposition, and ensure each firsts to be a great experience.
 
 
The team employs a variety of ML/AI techniques, spanning from causal ML meta learners, supervised ML, RL multi-armed bandits, genAI LLMs, transformer modeling on sequential data to deep learning embeddings to build impactful data products.
 
 
What the Candidate Will Need / Bonus Points
- What the Candidate Will Do - 
 
 
<ul><li>Build statistical, optimization, and machine learning models
</li><li>Develop innovative new earner incentives that earners for choosing our network and optimizing Uber's new earner incentives spend
</li><li>Optimize Uber's background check spend and onboarding funnel
</li><li>Design recommendation engines to recommend the most relevant earning opportunities and early lifecycle content
</li><li>Develop matching algorithms for driver to driver mentorship program
</li><li>Model and predict earner behaviors to improve earner experience throughout the onboarding funnel
</li><li>The team employs a variety of ML/AI techniques, spanning from causal ML meta learners, supervised ML, RL multi-armed bandits, genAI LLMs, transformer modeling on sequential data to deep learning embeddings to build impactful data products.
</li><li>Work closely with multi-functional leads to develop technical vision, new methodological approaches, and drive team direction.
</li><li>Collaborate with cross-functional teams such as product, engineering, operations, and marketing to drive ML system development end-to-end from conceptualization to final product.
</li></ul>- Basic Qualifications - 
 
 
<ul><li>PhD, Master or equivalent experience in Computer Science, Machine Learning, Operations Research, Statistics, or other related quantitative fields or related field
</li><li>2 years minimum of industry experience as a Machine Learning Engineer/Research Scientist with a strong focus on deep learning and probabilistic modeling.
</li><li>Proficiency in multiple object-oriented programming languages (e.g. Python, Go, Java, C++).
</li><li>Experience with any of the following: Spark, Hive, Kafka, Cassandra.
</li><li>Experience building and productionizing innovative end-to-end Machine Learning systems.
</li><li>Experience in exploratory data analysis, statistical modeling, hypothesis testing, and experimental design.
</li><li>Experience working with cross-functional teams(product, science, product ops etc).
</li></ul>- Preferred Qualifications - 
 
 
<ul><li>3+ years of industry experience in machine learning, including building and deploying ML models.
</li><li>Publications at industry recognized ML conferences.
</li><li>Experience in modern deep learning architectures and probabilistic modeling.
</li><li>Experience with optimization techniques, including reinforcement learning (RL), Bayesian methods, causal ML meta learners, genAI LLM.
</li>Expertise in the design and architecture of ML systems and workflows. 
<li>
</li></ul> 
 
 
 
For New York, NY-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.</div>

Machine Learning Engineer II

Apple

At Apple, we focus deeply on our customers&rsquo; experience. Apple Ads brings this same approach to advertising, helping people find exactly what they&rsquo;re looking for and helping advertisers grow their businesses! 
 
Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes-from small app developers to big, global brands. Because when advertising is done right, it benefits everyone! 
 
Description 
 
We're is looking for a highly skilled and motivated Machine Learning Engineer to join our Predictions group. We build the core machine learning models that power ad predictions and monetization across Apple&rsquo;s App Store and News platforms. The ideal candidate will bring deep expertise in machine learning, information retrieval, and large-scale modeling, and will thrive in a fast-paced, privacy-first environment. 
 
You&rsquo;ll work at the intersection of applied ML, deep learning, and retrieval systems-developing models that predict user interaction, optimize marketplace outcomes, and scale across billions of queries. You'll also explore and operationalize emerging techniques in Large Language Models (LLMs), Reinforcement Learning, and representation learning to advance Apple&rsquo;s ad prediction systems. 
 
&quot;,&quot;responsibilities&quot;:&quot;Design and implement ML models to improve predictions of user interaction, click-through rate (CTR), and conversion rate (CVR) 
 
Develop and optimize retrieval algorithms, leveraging techniques from classical IR and modern deep learning 
 
Contribute to core modeling areas such as deep neural networks, contextual bandits, multi-task learning, and LLM-based ranking signals 
 
Work with large-scale, distributed datasets to identify new signals and improve model accuracy and robustness 
 
Collaborate with cross-functional teams across engineering, infrastructure, and product to scale models to production 
 
Participate in designing and running large-scale experiments to validate new model architectures and learning strategies 
 
Preferred Qualifications 
 
MS or PhD, or equivalent experience, in Computer Science, Machine Learning, Artificial Intelligence, Information Retrieval, or a related field. 
 
Great foundation in information retrieval, including query-document matching, embedding-based ranking, and learning-to-rank algorithms is a plus 
 
Minimum Qualifications 
 
6+ years of experience applying machine learning and statistical modeling at scale, preferably in ad tech, recommender systems, or web-scale search/retrieval 
 
Deep experience with neural network architectures (e.g., Transformers, DNNs, RNNs) and training pipelines using TensorFlow, PyTorch 
 
Practical understanding of reinforcement learning, explore/exploit strategies, and bandit-based optimization 
 
Experience working with high-volume data pipelines, A/B testing infrastructure, and performance measurement at scale 
 
Proficient in Python and familiar with SQL, Scala, or Java for production environments 
 
Ability to translate abstract ideas into concrete, high-impact solutions 
 
Bachelor's, or equivalent experience, in Computer Science, Machine Learning, Artificial Intelligence, Information Retrieval, or a related field. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $212,000 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Senior Machine Learning Engineer - Ads Predictions

At Apple, we focus deeply on our customers&rsquo; experience. Apple Ads brings this same approach to advertising, helping people find exactly what they&rsquo;re looking for and helping advertisers grow their businesses! 
 
Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes-from small app developers to big, global brands. Because when advertising is done right, it benefits everyone! 
 
Description 
 
We are seeking an experienced Machine Learning Engineer to drive innovation in ad prediction, quality, and privacy-preserving signals. This role spans three critical areas: building large-scale prediction models, designing signals that respect user privacy, and ensuring ad quality that aligns with Apple&rsquo;s values of trust and transparency. You will set technical direction, lead complex initiatives, and mentor engineers while collaborating closely with research, infrastructure, and product teams. 
 
This role offers the opportunity to shape the future of privacy-first advertising at Apple. You&rsquo;ll work with some of the best engineers and researchers in the field, solve problems at massive scale, and deliver models that respect users while driving meaningful outcomes for advertisers.&quot;,&quot;responsibilities&quot;:&quot;10+ years of experience applying ML at scale in ads, recommender systems, content ranking, or related domains. 
 
Strong expertise in deep learning architectures (Transformers, LLMs, DNNs) and training frameworks (TensorFlow, PyTorch). 
 
Proven track record in prediction systems (CTR, CVR, or related) and explore/exploit strategies (bandits, RL). 
 
Experience with privacy-preserving ML (federated learning, differential privacy, homomorphic encryption, secure multiparty computation) is preferred. 
 
Familiarity with large-scale data pipelines, A/B testing infrastructure, and production experimentation. 
 
Strong coding skills in Python and production experience in at least one of: Scala, Java, C++. 
 
Ability to set technical direction, influence cross-functional stakeholders, and deliver business impact. 
 
Bachelor's in Computer Science, Machine Learning, or a related technical field. 
 
Preferred Qualifications 
 
MS or PhD, or equivalent experience, in Computer Science, Machine Learning, Artificial Intelligence, Information Retrieval, or a related field. 
 
Great foundation in information retrieval, including query-document matching, embedding-based ranking, and learning-to-rank algorithms is a plus 
 
Minimum Qualifications 
 
MS or PhD in Computer Science, Machine Learning, or related discipline. 
 
Published research or open-source contributions in ads, ranking, privacy-preserving ML, or large-scale prediction systems. 
 
Experience leading multi-team or cross-org initiatives with measurable business and user impact. 
 
Deep expertise in signals engineering for ads quality, trust &amp; safety, or search relevance. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $212,000 and $386,300, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Senior Staff Machine Learning Engineer - Ads Prediction, Signals & Quality

Two Sigma

<div>
 Position Summary
 
 
 Two Sigma is a leading quantitative investment management and trading firm. The company applies a scientific approach to investing, combining cutting-edge technology, artificial intelligence, data science, and quantitative research with rigorous human inquiry to capitalize on market opportunities and deliver alpha for investors.
 
 
 Our team of engineers, quantitative researchers, and data scientists looks beyond the traditional to test hypotheses and develop creative solutions to some of the world&rsquo;s most complex economic problems.
 
 
 We are looking for creative experts who are interested in applying general Machine Learning and specifically Deep Learning (complex neural networks, sequence models etc.), Large Language Models, Reinforcement Learning techniques to many types of problems in complex systems, but particularly those with large amounts of noisy data.
 
 
 
 This role is only open to MS with work experience and PhDs, both in their final year of study.
 
 
 
 
 You Will Take On The Following Responsibilities
 
 
 
 <ul>
 <li>
 Develop effective techniques and infrastructure, from the initial idea to the running prototypes and productionization
 </li>
 <li>
 You will write code, use the latest AI and Machine Learning tools, run experiments on state-of-the-art infrastructure and in the cloud, and generally develop techniques and processes to build predictive models for financial markets including but not limited to alpha modeling and trading tactics
 </li>
 <li>
 Partner with teams across Two Sigma to implement your ideas into our products
 </li>
 <li>
 Remain connected to the broader research community by partnering with internal and external collaborators and participate in relevant conferences
 
 
 </li>
 </ul>
 
 You Should Possess The Following Qualifications
 
 
 
 <ul>
 <li>
 Advanced degree in Computer Science, Engineering, or other STEM field, preferably in a PhD program, or in a Master&rsquo;s program with some prior work experience
 </li>
 <li>
 Excellent programming skills in Python (familiarity with Rust/Java/C++ is a plus) and deep knowledge of Tensorflow/PyTorch/JAX or similar
 </li>
 <li>
 Internships/work experience with Deep Learning, LLMs and/or Reinforcement Learning
 </li>
 <li>
 Background in Machine Learning techniques with large amounts of noisy data, curiosity in applying it to financial problems
 </li>
 <li>
 Relevant research experience (publications at NeurIPS, ICML, ICLR or similar are preferred)
 </li>
 <li>
 Experience with cloud environments and multi-machine CPU/GPU setups
 </li>
 <li>
 Experience with version control systems, regression/unit testing, code reviews, profiling
 </li>
 <li>
 Participation in open source community is a plus
 </li>
 <li>
 Being able to work well with others in teams
 
 
 </li>
 </ul>
 
 You Will Enjoy The Following Benefits
 
 
 
 <ul>
 <li>
 Core Benefits: Fully paid medical and dental insurance premiums for employees and dependents, competitive 401k match, employer-paid life &amp; disability insurance
 </li>
 <li>
 Perks: Onsite gyms with laundry service, wellness activities, casual dress, snacks, game rooms
 </li>
 <li>
 Learning: Tuition reimbursement, conference and training sponsorship
 </li>
 <li>
 Time Off: Generous vacation and unlimited sick days, competitive paid caregiver leaves
 </li>
 <li>
 Hybrid Work Policy: Flexible in-office days with budget for home office setup
 
 
 </li>
 </ul>
 The base pay for this role will be between $200,000 and $220,000. This role may also be eligible for other forms of compensation and benefits, such as a discretionary bonus, health, dental and other wellness plans and 401(k) contributions. Discretionary bonus can be a significant portion of total compensation. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their skills, qualifications and experience.
 
 
 We are proud to be an equal opportunity workplace. We do not discriminate based upon race, religion, color, national origin, sex, sexual orientation, gender identity/expression, age, status as a protected veteran, status as an individual with a disability, or any other applicable legally protected characteristics.
 
 
 Two Sigma is committed to providing reasonable accommodations to qualified individuals in accordance with applicable federal, state, and local laws.
 
 
 If you believe you need an accommodation, please visit our website for additional information.
</div>

AI Research Scientist - Campus Full-Time

At Apple, we work every day to create products that enrich people&rsquo;s lives. Apple Ads makes it possible for people around the world to easily access informative and imaginative content on their devices while helping publishers and developers promote and monetize their work. Today, our technology and services power advertising in Search Ads, App Store, and Apple News. Our platforms are highly-performant, deployed at scale, and setting new standards for enabling effective advertising while protecting user privacy. 
 
The Machine Learning Platform team&rsquo;s mission is to empower teams at Apple Ads to build and scale the innovative ML systems that deliver highly optimized advertising content to consumers. Are you a results-oriented and versatile engineer who can excel in an Agile environment? You will work closely with engineers and data scientists to design, develop, and build world-class platform capabilities that will enable Apple Ads teams to improve and scale our ML features, models, and applications. 
 
Description 
 
The ML Platform team is responsible for bringing numerous features to advertisers and consumers while simultaneously supporting scalable modeling and continuous experimentation by all Apple Ads teams. As a key contributor to this team, you will design and develop secure and scalable back-end systems. You will enjoy building high-performing, elegant machine learning systems from the ground up, in close partnerships with various teams. You will also possess keen judgment in selecting technologies and building the right solution for the interesting challenges we get to tackle here. You will have the opportunity to define and refine architectures to meet the unique ad network challenges we must solve. You will play a meaningful role building machine learning products which deliver on Apple's privacy commitments and change the way advertising works with data. 
 
Join us and contribute to a culture that emphasizes reliability, simplicity, and scalability. You will join a team of world-class machine learning engineers hungry to apply leading-edge technologies to deliver extraordinary experiences to our customers. We are one team, nurturing each other&rsquo;s growth and supporting each other in delivering for our customers! 
 
Preferred Qualifications 
 
PhD/MS/BS in Computer Science or related field with 9+ years of industry experience in building large-scale distributed software systems 
 
Minimum Qualifications 
 
10+ years of experience applying ML at scale in ads, recommender systems, content ranking, or related domains. 
 
Strong expertise in deep learning architectures (Transformers, LLMs, DNNs) and training frameworks (TensorFlow, PyTorch). 
 
Experience with privacy-preserving ML (federated learning, differential privacy, homomorphic encryption, secure multiparty computation) is preferred. 
 
Familiarity with machine learning libraries and frameworks 
 
Experience writing machine learning applications and mission-critical code for production machine learning systems 
 
Experience building and scaling cloud-based architectures 
 
Experience building AI/ML tooling and/or infrastructure 
 
Experience working on distributed systems where scalability and performance are critical 
 
Prior experience in model optimization is a huge plus 
 
Understanding of software engineering principles for maintainable code development 
 
Ability to communicate effectively, both written and verbal, with technical and non-technical multi-functional teams 
 
Ability to set technical direction and deliver business impact. 
 
Results oriented with a desire to work in a fast-paced and collaborative work environment 
 
Prior experience in advertising industry is a huge plus 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Staff Machine Learning Engineer

Stefanini Group

<div>
 
 Job Description
 
 
 
 Stefanini Group is looking for
 
 AI Engineer - Microsoft 365 Copilot Specialist
 
 for a globally recognized company!
 
 
 For interested applicants, click the apply button or you may reach out to
 
 Alfher Hidalgo at (248) 728-2627/Alfher.Hidalgo@stefanini.com
 
 for faster processing. Thank you!
 
 
 
 Job Summary
 
 
 
 We are looking for an AI Engineer who specializes in Microsoft 365 Copilot to help configure and optimize our AI-driven applications. The ideal candidate will have a deep understanding of the M365 platform, its features, and how they integrate seamlessly to enhance user experience. This role requires a professional who can ensure compliance with security protocols while maximizing the potential of AI tools within the organization.
 
 
 
 Key Responsibilities
 
 
 
 
 Copilot Configuration:
 
 Design, configure, and optimize Microsoft 365 Copilot to meet the specific needs of the organization, ensuring smooth integration with existing workflows and applications.
 
 
 
 Feature Integration:
 
 Collaborate with cross-functional teams to understand how various features within the M365 ecosystem work together, and develop strategies to enhance productivity through AI-driven solutions.
 
 
 
 Security Management:
 
 Assess and implement security measures related to the use of Copilot, ensuring compliance with organizational policies and industry standards. Stay updated on best practices for data privacy and security in AI applications.
 
 
 
 User Training and Support:
 
 Develop training materials and conduct workshops to educate team members on how to effectively utilize Copilot features, ensuring user adoption and proficiency.
 
 
 
 Monitoring and Optimization:
 
 Continuously monitor the performance of AI applications, analyze usage data, and identify opportunities for improvement to enhance functionality and user experience.
 
 
 
 Collaboration:
 
 Work closely with IT and security teams to address any potential risks associated with AI deployment and implement necessary controls.
 
 
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
 </li>
 <li>
 Proven experience working with Microsoft 365 Copilot, including configuration and feature integration.
 </li>
 <li>
 Strong understanding of the M365 ecosystem and its applications (e.g., Word, Excel, Teams, SharePoint).
 </li>
 <li>
 Knowledge of AI technologies and frameworks, with a focus on practical applications in a business context.
 </li>
 <li>
 Familiarity with security protocols and best practices related to AI and data handling.
 </li>
 <li>
 Excellent problem-solving skills and the ability to work collaboratively in a fast-paced environment.
 </li>
 <li>
 Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience in developing and implementing AI solutions in an enterprise environment.
 </li>
 <li>
 Certifications related to Microsoft technologies (e.g., Microsoft Certified: Azure AI Engineer Associate).
 </li>
 <li>
 Familiarity with machine learning frameworks and tools.
 
 
 </li>
 </ul>
</div>

AI Engineer - Microsoft 365 Copilot Specialist

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