ml scientist

KINDO

<div>Job Title: Senior Applied AI/ML Scientist (Deep Learning and Generative Models)

Company Overview: Kindo is an agent automation platform for DevOps and SecOps teams. We help organizations automate high-friction operational work using autonomous agents that run in the background &mdash; reliably, securely, and at scale.

We're ~40 people with strong customer traction, real enterprise revenue, and the infrastructure to support serious AI development. This isn't a side bet on AI. It's the entire company.

At the heart of our platform is DeepHat, Kindo's uncensored cybersecurity model. Built for real offensive reasoning, long-context analysis, and secure execution, DeepHat serves as the &quot;AI Brain&quot; of our platform. It is trained on real-world attack patterns and high-signal security data to power precise, autonomous workflows. As a member of the DeepHat team, you will be responsible for pushing the boundaries of what specialized LLMs can achieve in the realm of digital defense.

Job Description:

We are seeking a highly experienced Senior Applied AI/ML Scientist with a specialization in deep learning and generative models to join our dynamic team. In this role, you will play a pivotal part in the architecture and implementation of our AI modeling efforts, with a specific focus on post-training and fine-tuning large language models.

While this role requires deep technical expertise, we value a collaborative environment where good ideas flourish regardless of title. You will work within a team that empowers engineers to own their stack end-to-end. The ideal candidate has strong AI/ML fundamentals and can bridge the gap between theoretical research and practical production systems. You should be comfortable working with Agentic LLM usage and modern fine-tuning approaches, ranging from Supervised Fine-Tuning to Knowledge Distillation to RL, to create robust, reliable enterprise solutions.

You will be an early engineer at a high-growth startup, playing a significant role in building and bringing a new generative AI product to market. We are looking for a systems-thinker who cares as much about model evaluation and production stability as they do about algorithmic innovation.

Responsibilities:
<ul>
<li>Rigorous Evaluation (Evals): Architect, build, and maintain comprehensive evaluation pipelines. You believe that &quot;you can't improve what you don't measure,&quot; and you will be responsible for creating evals that accurately reflect production performance and agentic reliability.</li>
<li>Post-Training &amp; Fine-Tuning: Apply expert knowledge of model alignment and post-training strategies to tailor our in-house LLMs for enterprise capabilities. You should be adept at selecting and implementing the right technique for the job. Whether that is Supervised Fine-Tuning (SFT), Knowledge Distillation, PEFT, or leveraging alignment methods like Reinforcement Learning from Verifiable Rewards (RLVR) when appropriate.</li>
<li>Hands-on Data Engineering &amp; Strategy: Go beyond just &quot;using&quot; data. You will be responsible for the end-to-end data lifecycle&mdash;sourcing, cleaning, curating, and modifying datasets to maximize model effectiveness and domain specificity.</li>
<li>Training &amp; Inference Optimization: Utilize and optimize the open-source LLM ecosystem for the full model lifecycle. You will leverage distributed training tools (e.g., Accelerate, DeepSpeed/FSDP) and high-throughput serving engines (e.g., vLLM, TensorRT-LLM) to ensure efficiency from training to production.</li>
<li>End-to-End Ownership: Take a systems-level approach to AI. You will not just build models in isolation but will be responsible for the E2E lifecycle of the model, including how it integrates into production and interacts with the broader application.</li>
<li>Collaboration &amp; Mentorship: Work closely with cross-functional teams to translate product requirements into technical AI solutions. While this is an individual contributor role, you will be expected to mentor junior members, review code, and contribute to a culture where technical ideas are debated openly and constructively.</li>
</ul>
Required Qualifications:
<ul>
<li>Education: PhD or MS in Computer Science, Machine Learning, AI, or a related field, or equivalent practical experience.</li>
<li>Experience: 3-5+ years of experience in AI/ML with a strong focus on deep learning, generative models, and LLMs.</li>
<li>Effective AI Collaboration: You don't just &quot;use&quot; AI tools (e.g. Cursor, Claude Code, Devin, etc.); you know how to effectively partner with them to drive real efficiency. You know how to thoughtfully prompt, delegate, and iterate with these AI to achieve concrete productivity gains and genuinely accelerate your development process.</li>
<li>Evaluation Expertise: Demonstrated experience designing metrics and building evaluation harnesses for non-deterministic models. You understand that robust evals are the cornerstone of successful AI products.</li>
<li>Fine-Tuning Expertise: Deep understanding of the post-training landscape, with practical experience in techniques such as SFT, PEFT (LoRA/QLoRA), and Knowledge Distillation.</li>
<li>Applied Frameworks: Proficiency with the modern open-source LLM ecosystem. Experience with distributed training (e.g., Accelerate, FSDP, DeepSpeed) and high-level modeling libraries.</li>
<li>Strong Fundamentals: Deep conceptual understanding of the mathematical and architectural underpinnings of AI/ML (gradients, attention mechanisms, loss landscapes). While we don't code in raw TensorFlow/PyTorch daily, we value the first-principles understanding that comes with knowing these layers.</li>
<li>Systems Engineering: Experience with software engineering best practices and an ability to write clean, production-ready code. You should be comfortable with the &quot;Ops&quot; side of MLOps.</li>
<li>Problem Solving: Strong critical thinking skills with a pragmatic focus on shipping solutions that work for users, not just maximizing academic benchmarks.</li>
<li>Location: Hybrid Onsite in Venice, CA (2 days a week).</li>
</ul>
Preferred Qualifications:
<ul>
<li>LLM Production Experience: Practical experience deploying and maintaining LLMs in a production environment.</li>
<li>Advanced Alignment: Familiarity with emerging alignment research (e.g., DPO, RLVR) and an ability to determine when these complex methods add value over simpler baselines.</li>
<li>Agentic Concepts: Strong conceptual understanding of Agentic architectures (planning, tool use, ReAct loops, etc.).</li>
<li>Enterprise Context: Knowledge of enterprise security best practices and experience with Enterprise SaaS software.</li>
<li>Research Impact: A track record of staying current with arXiv papers and successfully translating a research concept into a working feature.</li>
</ul>
What We Offer:
<ul>
<li>Competitive salary (Range: $170k-$220k Base) and Equity</li>
<li>Comprehensive health, dental, and vision insurance</li>
<li>Unlimited vacation and paid time off policies</li>
<li>A chance to be part of a groundbreaking company shaping the future of generative AI</li>
</ul>
Company Culture:
<ul>
<li>Start-up and entrepreneurial mindset: High-energy, passionate, and willing to put in a bit of extra energy to ensure we succeed, but mindful of work-life balance, protecting weekends, and accommodating personal obligations. Full belief in the multi-billion dollar market opportunity in front of us.</li>
<li>Strong ownership culture: Complete ownership of core areas of responsibility, but also welcoming ideas and contributions from everyone. Everyone acts like product owners and contributes where they can provide value.</li>
<li>Fast-paced and action-oriented: Focus on high velocity, minimal processes, and utilizing existing solutions to maximize product development and minimize maintenance overhead. Focused on outcomes over hours. We work smarter, not harder.</li>
<li>Empathy, open-mindedness, and constructive feedback: Respect diverse working styles, encourage data-informed decisions, and build understanding and trust through direct conflict resolution</li>
<li>Reflective thinking and effectiveness: Balance thoughtful planning and discipline with action, prioritize finding solutions that meet customer needs over being right</li>
<li>Collaboration and support: Foster an environment where employees can work together, rely on each other, and support one another through challenges</li>
</ul>
If you are a passionate and talented AI researcher looking to make a meaningful impact in the generative AI space applied into end-user products, we would love to hear from you. Apply now and join our team of visionaries in creating the next unicorn company in the AI industry.</div>

Senior Applied AI/ML Scientist

Attentive.ai

<div>
 
 About Attentive.ai
 
 
 
 Attentive.ai is transforming the field services and construction industries with our flagship AI solution - Beam AI. Our platform empowers businesses to double their bidding capacity and accelerate growth through automation and intelligent insights.
 
 
 More than
 
 1k+ businesses
 
 across the U.S. and Canada already use our products to boost sales velocity and streamline operations. We have raised
 
 $30.5M in Series B funding
 
 , accelerating our mission to make advanced AI tools accessible, practical, and impactful in the real world. We are proudly Backed by Insight Partners, Peak XV (Surge), InfoEdge, Tenacity and Vertex Ventures.
 
 
 
 Position Description
 
 
 
 As an
 
 AI/ML Research Scientist,
 
 you will be an integral part of our AI research team focused on transforming the construction industry through cutting-edge deep learning, computer vision and NLP technologies. You will contribute to the development of intelligent systems for automated construction take-off and estimation by working with unstructured data such as blueprint, drawings (including SVGs), and PDF documents.
 
 
 In this role, you will support the end-to-end lifecycle of AI-based solutions &mdash; from prototyping and experimentation to deployment in production. Your contributions will directly impact the scalability, accuracy, and efficiency of our products.
 
 
 
 Roles &amp; Responsibilities
 
 
 
 <ul>
 <li>
 Build and deploy ML models for parsing and reasoning over construction blueprint PDFs - working with image, text and vector graphics modalities
 </li>
 <li>
 Design data pipelines for training, validation, and continuous improvement.
 </li>
 <li>
 Improve model accuracy, latency, and scalability for production workloads.
 </li>
 <li>
 Contribute to system architecture decisions for ML deployment and monitoring.
 </li>
 <li>
 Collaborate with cross-functional teams including software engineers, ML researchers, and product teams
 </li>
 <li>
 Write clean, scalable, and production-ready code
 
 
 </li>
 </ul>
 
 Skills &amp; Requirements
 
 
 
 <ul>
 <li>
 3&ndash;5 years of experience in applied AI/ML and research, preferably with focus on computer vision.
 </li>
 <li>
 PhD or Master's degree in deep learning, coupled with research experience focused on image modalities.
 </li>
 <li>
 Experience working with document understanding, OCR pipelines, or structured extraction systems is a plus.
 </li>
 <li>
 Deep understanding of unsupervised learning techniques like clustering, dimensionality reduction, and representation learning.
 </li>
 <li>
 Proficiency in Python and ML frameworks such as PyTorch, OpenCV, TensorFlow, and HuggingFace Transformers.
 </li>
 <li>
 Hands-on experience with model optimization techniques (e.g., quantization, pruning, knowledge distillation)
 </li>
 <li>
 Familiarity with LLM based systems and architectures
 </li>
 <li>
 Comfortable working in a fast-moving, ownership-driven environment.
 
 
 </li>
 </ul>
 
 Why Work With Us?
 
 
 
 <ul>
 <li>
 Be part of a visionary team building a first-of-its-kind AI solution for the construction industry.
 </li>
 <li>
 Exposure to real-world AI deployment and cutting-edge research in vision and multimodal learning.
 </li>
 <li>
 Culture that encourages ownership, innovation, and growth.
 </li>
 <li>
 Opportunities for fast learning, mentorship, and career progression.
 </li>
 </ul>
</div>

AI/ML Research Scientist

<div><div><h2 class="jobSectionHeader">Position Description:</h2>
The AI/ML Data Scientist serves as the technical backbone of the program analytics capability, responsible for building, training, and deploying machine learning models that transform raw vehicle sensor data into predictive maintenance insights. Operating within the Microsoft Azure MCEN and Jupiter/Advana cloud environments, this individual develops anomaly detection algorithms, predictive failure models, and health scoring systems that enable condition-based maintenance decisions.
 
The role requires privileged access to Government cloud computing environments, and the ability to translate complex data science into operationally understandable outputs that Marine maintainers can act upon.
 
This position works hand-in-hand with the Sr Maintenance Functional SME to ensure models are operationally validated, the Jr Maintenance SME &amp; Information Specialist to ensure outputs are expressed in maintainer language, and the Data Visualization Developer to ensure insights are presented effectively. 
This position is located in Quantico, VA.
</div><div><h2 class="jobSectionHeader">Your future duties and responsibilities:</h2>
Design, build, train, and deploy AI/ML models for predictive maintenance, anomaly detection, and equipment health scoring within Azure MCEN and Jupiter/Advana environments per PWS 3.3.1 
Develop and maintain the data Extract, Transform, and Load (ETL) pipeline from data logger ingestion through the Azure cloud stack to dashboard outputs per PWS 3.3.2 
Analyze CAN bus data (J1939/J1708 protocols) including thermal analysis, fuel system diagnostics, vibration/shock data, and component operating parameters 
Collaborate with the Sr Maintenance Functional SME to validate model outputs against real-world maintenance outcomes and refine prediction accuracy targets (&gt;80% positive predictive value) 
Optimize cloud architecture for scalability as the program expands from initial deployment to 3,00010,000+ data loggers per PWS 3.3.7 
Incorporate additional data sources into the program data pipeline including GCSS-MC maintenance records, EFAS fluid analysis, and enterprise logistics data per PWS 3.3.8 
Support current dashboards, data pipelines, policies, and procedures from data entry point to Jupiter/Advana per PWS 3.3.4 
Develop and refine data query frameworks that enable Marine Corps data analysis requests for ad-hoc reporting and trend analysis 
Perform daily monitoring of data processes during normal business hours to proactively identify pipeline issues per PWS 3.3.7 
Support Jira task tracking, Wiki management, onboarding of contractor personnel to cloud environments, and data governance policies per PWS 3.3.7 
Leverage Microsoft Azure's native AI/ML capabilities including Azure Machine Learning for model training and deployment, and DataBricks for advanced analytics
</div><div><h2 class="jobSectionHeader">Required qualifications to be successful in this role:</h2>
Master's degree in Data Science, Computer Science, Applied Mathematics, or related quantitative field (or Bachelor's with 5+ additional years of experience) 
5+ years of experience developing and deploying ML models in production environments 
Proficiency in Python, R, or equivalent, with experience in scikit-learn, TensorFlow, PyTorch, or similar frameworks 
Experience with Microsoft Azure cloud services, Azure Machine Learning, and DataBricks 
Experience building ETL pipelines and working with structured and unstructured sensor/IoT data 
Security+ certification or equivalent IAT-II certification (or ability to obtain within 90 days of start) 
Active Secret clearance 
Experience working in DoD or Federal Government cloud environments 
Preferred Qualifications 
Experience with CAN bus data, vehicle telemetry, or industrial IoT sensor analytics 
Familiarity with predictive maintenance, condition monitoring, or reliability engineering domains 
Experience with Qlik, Power BI, or similar visualization tools in government environments 
Prior experience on the Marine Corps Enterprise Network (MCEN) or with Azure Government cloud 
Understanding of DoD Cybersecurity Framework (RMF), NIST 800-53 controls, and STIG compliance 
Experience with the Jupiter/Advana analytics environment 
- 
CGI is required by law in some jurisdictions to include a reasonable estimate of the compensation range for this role. The determination of this range includes various factors not limited to skill set, level, experience, relevant training, and licensure and certifications. To support the ability to reward for merit-based performance, CGI typically does not hire individuals at or near the top of the range for their role. Compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range for this role in the U.S. is $79,600.00 - $153,300.00. 
CGI Federal's benefits are offered to eligible professionals on their first day of employment to include:
 
.Competitive compensation 
.Comprehensive insurance options 
.Matching contributions through the 401(k) plan and the share purchase plan 
.Paid time off for vacation, holidays, and sick time 
.Paid parental leave 
.Learning opportunities and tuition assistance 
.Wellness and Well-being programs 
#CGIFederalJob 
#LI-MG4 
#ClearanceJobs 
</div><div><h2 class="jobSectionHeader">Skills:</h2>
<ul><li>Data Visualisation</li>
<li>Development (Fed)</li>
<li>Python</li>
<li>Scikit-Learn</li>
</ul></div><div><h2 class="jobSectionHeader">What you can expect from us:</h2>
Together, as owners, lets turn meaningful insights into action. 
 
Life at CGI is rooted in ownership, teamwork, respect and belonging. Here, youll reach your full potential because 
 
You are invited to be an owner from day 1 as we work together to bring our Dream to life. Thats why we call ourselves CGI Partners rather than employees. We benefit from our collective success and actively shape our companys strategy and direction. 
 
Your work creates value. Youll develop innovative solutions and build relationships with teammates and clients while accessing global capabilities to scale your ideas, embrace new opportunities, and benefit from expansive industry and technology expertise. 
 
Youll shape your career by joining a company built to grow and last. Youll be supported by leaders who care about your health and well-being and provide you with opportunities to deepen your skills and broaden your horizons.
 
 
Come join our teamone of the largest IT and business consulting services firms in the world. 
 
Qualified applicants will receive consideration for employment without regard to their race, ethnicity, ancestry, color, sex, religion, creed, age, national origin, citizenship status, disability, pregnancy, medical condition, military and veteran status, marital status, sexual orientation or perceived sexual orientation, gender, gender identity, and gender expression, familial status or responsibilities, reproductive health decisions, political affiliation, genetic information, height, weight, or any other legally protected status or characteristics to the extent required by applicable federal, state, and/or local laws where we do business. 
 
CGI provides reasonable accommodations to qualified individuals with disabilities. If you need an accommodation to apply for a job in the U.S., please email the CGI U.S. Employment Compliance mailbox at US_Employment_Compliance@cgi.com. You will need to reference the Position ID of the position in which you are interested. Your message will be routed to the appropriate recruiter who will assist you. Please note, this email address is only to be used for those individuals who need an accommodation to apply for a job. Emails for any other reason or those that do not include a Position ID will not be returned. 
 
We make it easy to translate military experience and skills! to be directed to our site that is dedicated to veterans and transitioning service members. 
 
All CGI offers of employment in the U.S. are contingent upon the ability to successfully complete a background investigation. Background investigation components can vary dependent upon specific assignment and/or level of US government security clearance held. Dependent upon role and/or federal government security clearance requirements, and in accordance with applicable laws, some background investigations may include a credit check. CGI will consider for employment qualified applicants with arrests and conviction records in accordance with all local regulations and ordinances. 
 
CGI will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with CGIs legal duty to furnish information.</div></div>

AI/ML Data Scientist

General Motors (GM)

<div>Job Description
At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We&rsquo;re turning today&rsquo;s impossible into tomorrow&rsquo;s standard &mdash;from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features.
Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale..
The Role
Our Product Safety Data Analytics team is seeking an experienced AI/ML Data Scientist with hands-on experience in the full end to end data science lifecycle for artificial intelligence &amp; machine learning.
This role requires programming and statistical techniques to solve complex problems and work within a team framework on new AI/ML solutions.
If you're passionate about driving innovation through AI/ML and have experienced delivering solutions to your customers, this role offers an exciting opportunity to contribute to impactful projects in a dynamic team environment. 
 
As an AI/ML Data Scientist, you will be responsible for working with our customers to understand their challenges and needs, develop new machine learning solutions, work with ML Ops in a cloud environment, develop proof of concepts for new generative AI solutions and Agentic AI solutions.
What You&rsquo;ll Do
<ul><li>Work with our existing business partners to identify opportunities for new AI/ML solutions to enhance processes and enable our team members to be more efficient
</li><li>Train new machine learning models to solve complex business problems.
</li><li>Prototype new AI solutions, including Generative AI, to solve business problems.
</li><li>Develop new Agentic AI solutions to streamline business process
</li><li>Ehnance existing model solutions as business and technology continues to evolve
</li><li>Provide guidance on business problems using statistical methods and can craft ad-hoc reports to share findings and recommendations with business partners.
</li><li>Build statistical models that depict company-wide trends.
</li><li>Perform testing and validation of data sets.
</li><li>Work on and refine storytelling skills to convey ideas and results to leadership, customers and stakeholders
</li></ul>Your Skills &amp; Abilities (Required Qualifications)
<ul><li>Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
</li><li>5+ years of experience in machine learning, engineering, data science, or a related field
</li><li>Looking for experience in the following:
<ul><li>Programming &amp; Frameworks : Python, R, Java, PySpark, PyTorch, TensorFlow, Scikit-learn, LangChain, SQL
</li><li>Machine Learning &amp; AI : Large Language Models (LLMs), Generative AI, RAG, Generative AI, Deep learning, Reinforcement Learning, Natural Language Processing (NLP), SVM, XGBoost, Random Forest, Decision Trees, Clustering
</li><li>Data Engineering : Databricks, Hadoop, SQL, Data Pipelines, Data Preprocessing &amp; Feature Engineering
</li><li>Cloud &amp; Big Data Platforms: ( Preferred Microsoft Azure (Data Lake, Machine Learning, Databricks), Nice to Have (AWS (S3, SageMaker, Bedrock) or Google Cloud Platform (BigQuery, Dataflow, AI Platform) )
</li><li>Deployment &amp; MLOps: MLflow , Model Monitoring &amp; Versioning, Docker &amp; Kubernetes, GitHub , Jira
</li><li>Data Analysis &amp; Visualization : Tableau, PowerBI, Pandas, NumPy
</li></ul></li><li>Proven track record delivering AI/ML solutions to customers that get continued usage and drive value
</li><li>Excellent communication and collaboration skills, with the ability to work effectively in a team environment
</li><li>Strong problem-solving mindset and a proactive attitude towards learning and self-improvement
</li></ul>What Will Give You A Competitive Edge (Preferred qualifications)
<ul><li>Deep knowledge of GM&rsquo;s Data Ecosystem
</li><li>Deep knowledge of GM&rsquo;s Cloud Technology Stack for Data Science
</li><li>Deep knowledge of Global Product Safety&rsquo;s SFI Process
</li></ul><ul><li>Extensive NLP solutions from business problem statement to deployment and ongoing optimization
</li><li>Expertise with Large Language Models solutions from business problem statement to cloud deployment that have provided significant incremental business value
</li><li>Experience with generative AI solutions that you have developed and deployed into a production environment that have provided significant incremental business value
</li></ul>&amp;#xa;&amp;#xa;GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc).&amp;#xa;&amp;#xa;This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}.&amp;#xa;&amp;#xa;This job may be eligible for relocation benefits.&amp;#xa;&amp;#xa;
About GM
Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.
Why Join Us
We believe we all must make a choice every day &ndash; individually and collectively &ndash; to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.
Benefits Overview
From day one, we're looking out for your well-being&ndash;at work and at home&ndash;so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources .
Non-Discrimination and Equal Employment Opportunities (U.S.)
General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.
All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.
We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire .
Accommodations
General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.</div>

AI/ML Data Scientist (GPSSC)

Vanguard

<div><div>Leads and executes deep dive diagnostic, predictive, and prescriptive analytics to support data-driven business decision making. Mentors and develops junior data scientists and analysts.</div><div>
Role Summary
This role leads and executes deep dive diagnostic, predictive, and prescriptive analytics to support data-driven business decision making, while mentoring junior data scientists and analysts, and applying advanced data science and big data mining techniques to uncover trends, inform strategic initiatives, and drive innovation across diverse business functions. 
Responsibilities<ul><li>
Develops complex queries and performs extensive programming to access, transform, and prepare data for statistical modeling.</li><li>
Leads and executes deep dive diagnostic, predictive, and prescriptive analytics to support data-driven business decision making. Mentors and develops junior data scientists and analysts.</li><li>
Identifies and diagnoses data inconsistencies and errors, documents data assumptions, and forages to fill data gaps.</li><li>
Engages with internal stakeholders to understand and probe business processes in order to develop hypotheses. Brings structure to requests and translates requirements into an analytic approach.</li><li>
Guides test design, research design, and model validation. Provides statistical consultation services. Serves as the analytics expert on cross functional teams for large strategic initiatives and contributes to the growth of the Vanguard analytic community.</li><li>
Prepares and delivers insight presentations and action recommendations. Communicates complex analytical findings and implications to business leaders.</li><li>
Participates in special projects and performs other duties as assigned.</li><li>
Designs scalable data mining models and reporting protocols to identify trends and patterns in massive datasets.</li><li>
Applies modern and emerging data science techniques to solve business problems across functions such as marketing, economics, and operations.</li><li>
Contributes to the advancement of analytics through exploratory research and application of cutting-edge statistical theory.</li></ul> 
Qualifications and Skills<ul><li>
Minimum 8 years of experience in data science, predictive analytics, or advanced statistical modeling roles</li><li>
Bachelor&rsquo;s degree (B.E./B.Tech) in Analytics, Applied Mathematics, Economics, Statistics, or Computer Science, or a Master&rsquo;s degree/Diploma in a related quantitative field</li><li>
Expertise in programming with Python, R, or SQL; hands-on experience with machine learning libraries (e.g., Scikit-learn, TensorFlow); strong understanding of data pipelines, data wrangling, and statistical techniques; experience in big data environments (Spark/Hadoop); familiarity with visualization tools like Tableau or Power BI.</li></ul>
Special Factors
Sponsorship
Vanguard is offering visa sponsorship for this position.
About Vanguard
At Vanguard, we don't just have a mission&mdash;we're on a mission.
To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.
How We Work
Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.</div></div>

<div>We help the world run better 
 
At SAP, we enable you to bring out your best. Our company culture is focused on collaboration and a shared passion to help the world run better. How? We focus every day on building the foundation for tomorrow and creating a workplace that embraces differences, values flexibility, and is aligned to our purpose-driven and future-focused work. We offer a highly collaborative, caring team environment with a strong focus on learning and development, recognition for your individual contributions, and a variety of benefit options for you to choose from. 
Summary:
We are searching for an experienced Expert AI/ML Applied Data Scientist to join our newly formed ABAP Foundation Model team in New Port Beach. This dynamic team is at the forefront of SAP&rsquo;s cloud transformation efforts, leveraging large language models to accelerate our customers&rsquo; data and code transformation. The team collaborates closely with established teams in Europe and India, various SAP stakeholders, UC Irvine, and early adopter customers. You will play a key role in shaping our research collaboration with UC Irvine and coordinating with data science leads of ABAP Foundation Model teams globally. 
What you&rsquo;ll do:<ul><li>
Model Development: Oversee the development, fine-tuning, and integration of foundation models into SAP solutions to streamline cloud transformation journeys.</li><li>
Collaboration: Engage with stakeholders in different teams at SAP as well as early adopter customers and research collaborations.</li><li>
Leadership: Mentor and lead junior and senior data scientists, fostering a culture of innovation and excellence.</li></ul> 
What you bring:<ul><li>
Educational Background: PhD or Master&rsquo;s degree in Computer Science, Data Science, Machine Learning, or a related field.</li><li>
Experience: 7+ years of experience in data science, with a proven record of leading projects to success.</li><li>
Technical Proficiency: Expertise in deep learning, large language models, and significant experience with deep learning frameworks such as PyTorch and Tensorflow.</li><li>
Communication: Exceptional verbal and written communication skills.</li><li>
Leadership: Demonstrated ability to lead and mentor teams and drive strategic initiatives.</li></ul> 
Meet your team:
The ABAP Foundation Model team is pioneering AI innovations within the SAP ABAP ecosystem. It is an integral part of the Generative AI foundation within Business AI at SAP. We focus on creating and refining our own Foundation Models using SAP Business Data, pushing the boundaries of what&rsquo;s possible with AI in business applications. By joining our team, you&rsquo;ll be an integral part of shaping the future of AI at SAP and driving significant advancements in the field. 
 
#LI-CD1 
Bring out your best
SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best. 
We win with inclusion
SAP&rsquo;s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone &ndash; regardless of background &ndash; feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better and more equitable world. 
SAP is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to the values of Equal Employment Opportunity and provide accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: Careers@sap.com. 
For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training. 
EOE AA M/F/Vet/Disability
Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, age, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability. 
Compensation Range Transparency: SAP believes the value of pay transparency contributes towards an honest and supportive culture and is a significant step toward demonstrating SAP&rsquo;s commitment to pay equity. SAP provides the annualized compensation range inclusive of base salary and variable incentive target for the career level applicable to the posted role. The targeted combined range for this position is 164200 - 374200 (USD) USD. The actual amount to be offered to the successful candidate will be within that range, dependent upon the key aspects of each case which may include education, skills, experience, scope of the role, location, etc. as determined through the selection process. Any SAP variable incentive includes a targeted dollar amount and any actual payout amount is dependent on company and personal performance. Please reference this link for a summary of SAP benefits and eligibility requirements: SAP North America Benefits. 
Requisition ID: 404236 | Work Area:Software-Design and Development | Expected Travel: 0 - 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations: #LI-Hybrid</div>

Expert AI/ML Applied Scientist - Generative AI

Ispeck Digital Solutions

<div><div>Location: Kolkata (On-site) 
Experience: 4-5 Years 
Education: Master&rsquo;s degree in computer science /engineering/ data science 
Employment Type: Full-Time 
Role Overview

We are seeking a highly skilled Data Scientist with expertise in Large Language Models (LLM), Machine Learning, Generative AI, and Agentic AI frameworks to design, build, and deploy intelligent AI solutions, intelligent AI agents and scalable ML systems that integrate with enterprise application.

The ideal candidate will combine strong fundamentals in ML modeling with hands-on experience in LLM integration, RAG pipelines, AI agents, and production-grade ML deployment.

Additionally, S/HE should be a team player with strong communication skill and good command of English.
<div>
</div>Key Responsibilities
<ul>
<li>Build, train, and deploy advanced ML and AI models (supervised, unsupervised, deep learning)</li>
<li>Design and implement LLM-powered AI agents and multi-agent workflows</li>
<li>Develop and optimize Retrieval-Augmented Generation (RAG) pipelines</li>
<li>Implement end-to-end ML lifecycle: data ingestion, feature engineering, training, deployment, monitoring</li>
<li>Fine-tune models and optimize prompts for performance and cost</li>
<li>Deploy production-grade AI systems using Docker, Kubernetes, and cloud platforms</li>
<li>Monitor models for drift, bias, hallucinations, and performance degradation</li>
<li>Collaborate with product and engineering teams to translate business problems into AI-driven solutions</li></ul><div> 
</div>Core ML &amp; AI Expertise (Must have)

Machine Learning
<ul>
<li>Regression, Classification (Logistic, Random Forest, XGBoost, LightGBM)</li>
<li>Clustering (K-Means, DBSCAN)</li>
<li>Time Series (ARIMA, Prophet, LSTM)</li>
<li>Anomaly Detection (Isolation Forest, One-Class SVM)</li>
<li>Recommender Systems</li>
</ul>
Deep Learning &amp; NLP
<ul>
<li>CNNs, RNNs, LSTM, Transformers</li>
<li>BERT and Transformer-based architectures</li>
<li>Embeddings and semantic search</li>
</ul>
Generative AI &amp; Agentic Systems
<ul>
<li>LLM API integration (OpenAI, Anthropic, AWS Bedrock)</li>
<li>Prompt engineering (few-shot, chain-of-thought, structured prompting)</li>
<li>LLM fine-tuning and evaluation</li>
<li>Agent frameworks: LangChain, LlamaIndex, AutoGen, CrewAI</li>
<li>Tool calling &amp; function execution frameworks</li>
<li>Vector databases (Pinecone, Weaviate, FAISS)</li>
<li>Hybrid search (semantic + keyword)</li>
</ul>
Technical Stack
<ul>
<li>Languages: Python (Primary), SQL</li>
<li>ML Frameworks: Scikit-learn, TensorFlow, PyTorch</li>
<li>API Frameworks: FastAPI / Flask</li>
<li>MLOps: MLflow, CI/CD pipelines, model monitoring</li>
<li>Cloud: AWS (Bedrock, SageMaker), Azure OpenAI, GCP AI</li>
<li>Infrastructure: Docker, Kubernetes</li>
</ul>
Required Qualifications
<ul>
<li>4-5 years of demonstrated experience in Data Science / ML</li>
<li>1&ndash;2+ years of hands-on experience with LLM-based systems</li>
<li>Strong background in statistics, probability, and model evaluation</li>
<li>Experience deploying AI systems in production environments</li>
</ul>
Preferred Skills (Good to have)
<ul>
<li>Experience with open-source LLMs (Llama, Mistral)</li>
<li>Knowledge of RLHF / alignment techniques</li>
<li>Experience building AI copilots or enterprise automation agents</li>
<li>Exposure to Responsible AI, governance, and security</li></ul> 
** Candidates who meet the above criteria and are available to join immediately will be given preference.</div></div>

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Expert AI/ML Applied Scientist - Generative AI

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