machine learning scientist

Field of Talent

<div><div>Lead Machine Learning Scientist &ndash; Sleep &amp; Physiologic Signal Modeling</div><div></div><div> 
We are currently pipelining for a Lead Machine Learning Scientist role slated for Q2 2026. This leader will spearhead the development of advanced ML models designed to extract clinically significant risk signals from multi-modal physiological data. This role leads the intelligence layer of a novel at-home physiologic monitoring platform designed to support clinical decision-making in perioperative care.</div><div></div><div> 
This is a hands-on technical leadership role with direct impact on a federally funded Phase I program.</div><div></div><div> 
Contractual Engagement: 450 hours (approx. 2.5&ndash;3 months) in the United States (Remote)</div><div></div><div> 
Why This Opportunity Is Different</div><ul>
<li>Technical ownership &ndash; You lead the ML strategy for the intelligence layer, not just a slice of it</li>
<li>Clinically grounded ML &ndash; Direct collaboration with sleep medicine and anesthesia experts</li>
<li>NIH-backed impact &ndash; Your work drives feasibility results for a Phase I grant</li>
<li>Signal-rich problems &ndash; EEG, ECG, oximetry, motion, real data, real complexity</li>
<li>Flexible work options &ndash; Remote contract work that balances focus, collaboration, and flexibility</li>
<li>Growth&ndash; Contribute to early-stage product design with potential to extend to long-term roles</li> 
</ul><div></div> 
<div>What You&rsquo;ll Do</div><ul>
<li>Design, build, and validate ML pipelines for multi-signal physiologic data modeling</li>
<li>Develop robust feature extraction methods for EEG, ECG, pulse oximetry (SpO₂), and motion signals</li>
<li>Train and evaluate models to estimate clinically relevant metrics such as arousal burden, hypoxic burden, arousal threshold, and airway instability</li>
<li>Collaborate closely with clinical domain experts (sleep medicine and anesthesia) to translate physiologic signals into operational risk signatures</li>
<li>Assess model performance, interpretability, and generalizability across patient populations</li>
<li>Prepare technical methods, results, and documentation for NIH deliverables, publications, and regulatory-facing materials</li> 
</ul><div></div> 
<div>What You Bring</div><ul>
<li>Prefer MS or PhD in Machine Learning, AI, Biomedical Engineering, Computational Neuroscience</li>
<li>Hands-on experience modeling physiologic signals (EEG, ECG, PPG, SpO₂, motion)</li>
<li>Strong background in deep learning architectures (CNNs, LSTMs, Transformers)</li>
<li>Comfort owning ambiguous technical problems end-to-end</li>
<li>Bonus: experience in sleep medicine, anesthesia, or medical devices</li> 
</ul><div></div> 
<div>About: Early-stage medical device company developing a patented, skin-worn wearable that enables sleep-lab&ndash;level physiologic monitoring, with a focus on identifying undiagnosed sleep apnea before surgery. Addressing a major perioperative safety gap where a large percentage of patients undergo anesthesia with undetected sleep-related risk. Building tech that directly improves clinical decision making and patient outcomes. Small team, highly technical, mission-driven, working with wearable devices, physiologic signal processing, ML, and clinical research through federally funded programs.</div><div></div><div> 
By applying for this job, you agree that we can text you (Standard Rates Apply).</div></div>

Lead Machine Learning Scientist

GoDaddy

<div><div><ul><li>R022738
</li></ul></div><div><ul><li>Gurugram, Haryana, India
</li></ul></div><div></div><div><ul><li>Engineering
</li></ul></div><div><ul><li>Regular</li></ul></div></div><div></div>
 <div>Location Details: Gurugram, India

At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.
Hybrid: This is a hybrid position. You&rsquo;ll divide your time between working remotely from your home and an office, so you should live within commuting distance. Hybrid teams may work in-office as much as a few times a week or as little as once a month or quarter, as decided by leadership. The hiring manager can share more about what hybrid work might look like for this team.

Join Our Team

Our core machine learning team applies large-scale data to power various business areas, and our goal is to build cohesive navigation experience across channels and web pages, to help simplify and improve the shopping experience for everyday entrepreneurs across the world to quickly find what they need on our website. We will roll up our sleeves to build best in class of personalization to offer most relevant products and prices at the right time. Your contributions will affect millions of our customers and will have a direct impact on our business results. Whether you&rsquo;re passionate about crafting highly scalable systems or developing seamless customer experiences, we have a role for you. Join us and build the future of software at GoDaddy!

What you'll get to do...
<ul>
<li>You will provide technical leadership, identify and evaluate new technologies, tools, and frameworks and incorporate them into the team's workflow and processes.</li>
<li>You will coordinate large scale and complex machine learning projects in production and cooperate with various teams to define project scope, goals, and success metrics.</li>
<li>You will collaborate extensively with internal partners, program management, and engineering team to ensure that solution meet business needs, permit valid inferences and have functional feasibility.</li>
<li>You will communicate results in a comprehensible manner to all levels of the company.</li>
<li>You will mentor junior scientists in the team.</li>
</ul>
Your experience should include...
<ul>
<li>3+ years of industrial experience in deep learning and software development, with strong algorithm design skills.</li>
<li>Hands-on experience with Deep Neural Network technologies, LLMs, and agentic AI.</li>
<li>Proficient in programming languages such as Python or Java.</li>
<li>Experience with machine learning platforms (e.g., PyTorch) and AWS.</li>
<li>Familiarity with large-scale data analytics (e.g., Spark) and an MS or PhD or equivalent experience in computer science or a related quantitative field is required.</li></ul> 


We've got your back... We offer a range of total rewards that may include paid time off, retirement savings (e.g., 401k, pension schemes), bonus/incentive eligibility, equity grants, participation in our employee stock purchase plan, competitive health benefits, and other family-friendly benefits including parental leave. GoDaddy&rsquo;s benefits vary based on individual role and location and can be reviewed in more detail during the interview process.

We also embrace our diverse culture and offer a range of Employee Resource Groups (Culture). Have a side hustle? No problem. We love entrepreneurs! Most importantly, come as you are and make your own way.

About us... GoDaddy is empowering everyday entrepreneurs around the world by providing the help and tools to succeed online, making opportunity more inclusive for all. GoDaddy is the place people come to name their idea, build a professional website, attract customers, sell their products and services, and manage their work. Our mission is to give our customers the tools, insights, and people to transform their ideas and personal initiative into success. To learn more about the company, visit About Us.

At GoDaddy, we know diverse teams build better products&mdash;period. Our people and culture reflect and celebrate that sense of diversity and inclusion in ideas, experiences and perspectives. But we also know that&rsquo;s not enough to build true equity and belonging in our communities. That&rsquo;s why we prioritize integrating diversity, equity, inclusion and belonging principles into the core of how we work every day&mdash;focusing not only on our employee experience, but also our customer experience and operations. It&rsquo;s the best way to serve our mission of empowering entrepreneurs everywhere, and making opportunity more inclusive for all. To read more about these commitments, as well as our representation and pay equity data, check out our Diversity and Pay Parity annual report which can be found on our Diversity Careers page.

GoDaddy is proud to be an equal opportunity employer. GoDaddy will consider for employment qualified applicants with criminal histories in a manner consistent with local and federal requirements. Refer to our full EEO policy.

Our recruiting team is available to assist you in completing your application. If they could be helpful, please reach out to myrecruiter@godaddy.com.

GoDaddy doesn&rsquo;t accept unsolicited resumes from recruiters or employment agencies.</div>

Senior Machine Learning Scientist

black.ai

At Sonder, we believe that every person deserves to feel safe, supported, and empowered to be at their best - wherever they are. That's why we're redefining workplace health, safety, and wellbeing through a seamless blend of technology and human expertise. Sonder's mobile platform provides 24/7, real-time support from a dedicated team of safety, medical, and mental health professionals - ensuring that our members receive immediate care when they need it most. In critical situations, we go beyond digital support, offering on-the-ground assistance to manage time-sensitive incidents. By harnessing real-time insights, we enable organisations to take proactive steps toward a healthier, safer future, which leads directly to tangible bottom-line business outcomes. An Exciting Time to Join Sonder! Since our founding in 2017, Sonder has experienced rapid growth, expanding operations across Australia, New Zealand, and the UK. Backed by Australia's leading venture capital firms, Seek and Blackbird, we are well-capitalised and on a mission to scale globally, partnering with corporations, educational institutions, and government agencies to transform workplace wellbeing at scale. Our impact and scale: <ul> <li>1,000,000+ members across multiple countries</li> <li>200+ team members, plus an extensive network of on-the-ground responders</li> </ul> If you're passionate about using technology and human expertise to drive meaningful change, join us in shaping the future of workplace wellbeing! Role Summary Are you a recent PhD graduate or Postdoctoral researcher passionate about applying cutting edge AI to solve real world problems? Join Sonder as an Applied Machine Learning Scientist/Engineer - focusing on LLM Research & Fine Tuning Engineering, and help us build a new generation of AI systems that directly impact human well being and safety. This is a unique opportunity for a PhD level candidate to apply their deep academic knowledge to a mission driven environment. This role is distinct from typical AI tooling or RAG based roles. We are not seeking candidates whose primary experience is in building vector search systems or integrating off the shelf APIs. Instead, we require deep, hands on expertise with the internal workings of large language models. Your work will be instrumental in developing our personalisation engine and fine tuning state of the art open source LLMs like LLaMa, Mistral, and DeepSeek. Your research will translate directly into creating specialised LLMs that provide empathetic, life saving support to our members. We're looking for someone who thrives on technical challenges and wants to see their expertise translate into a positive, tangible impact. Key Responsibilities <ul> <li>Research, fine tune, and optimise open source LLMs using techniques such as PEFT, LoRA, and QLoRA to build our proprietary AI models.</li> <li>Contribute to the design and implementation of our personalisation and recommendation engines to deliver tailored, proactive support.</li> <li>Develop and maintain robust machine learning pipelines for model training, evaluation, and deployment.</li> <li>Collaborate closely with cross functional teams, including product managers, software engineers, and mental health professionals, to translate research into effective product features.</li> <li>Stay current with the latest advancements in AI and LLM research, and apply new techniques to improve our systems.</li> <li>Publish and/or present research findings at conferences or in academic journals where appropriate, contributing to the broader AI community.</li> </ul> Key Qualifications <ul> <li>A recently completed PhD or Postdoctoral experience in Machine Learning, AI, Computer Science, or a closely related quantitative field.</li> <li>Deep theoretical and practical understanding of Transformer architectures, attention mechanisms, and training dynamics.</li> <li>Hands on experience fine tuning open source LLMs (e.g., LLaMa, Mistral, DeepSeek).</li> <li>Strong computer science fundamentals and coding proficiency in Python.</li> <li>Solid experience with deep learning frameworks such as PyTorch or TensorFlow.</li> <li>A profound passion for applying AI to high impact, meaningful domains such as mental health and well being.</li> </ul> Candidates with primary experience limited to building Retrieval Augmented Generation (RAG) systems or MLOps tooling are not a suitable fit for this specific role. Nice to Have <ul> <li>Experience with distributed training techniques for large models.</li> <li>Familiarity with cloud based machine learning stacks (e.g., AWS, GCP).</li> <li>A track record of peer reviewed publications in top tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR, AAAI, ACL).</li> </ul> Eligibility <ul> <li>The right to work full time in Australia</li> <li>Located within commuting distance to our Sydney office at the time of commencement.</li> </ul> Impact & Growth Your work at Sonder will go beyond just optimising models; it will directly contribute to saving lives and improving mental well being on a global scale. This role offers the opportunity to shape our core AI technology from the ground up while growing as a leader in a supportive, mission driven environment. You will have the freedom to explore new research ideas and the resources to see them through to deployment, making a tangible difference in the world. Why Join Sonder? At Sonder, we thrive in a fast paced, high performance environment with a strong commitment to our people. Our team is a collaborative, vibrant group of passionate professionals, dedicated to making a real impact on people's lives every day. <ul> <li>Hybrid and flexible working environment. Enjoy the perfect balance of in office collaboration and work from home flexibility, empowering you to optimise your productivity and work life balance.</li> <li>Gain free access to the Sonder app for you and your family, offering 24/7 on demand support for health, wellbeing, and safety.</li> <li>$1000 annual contribution as part of your development plan + 2 days of study leave</li> <li>Paid parental leave with an attractive return to work policy, 12 weeks for Primary Carers and 4 weeks for Secondary Carers, plus our Primary Carers return to work at 80% for the first 3 months at full pay.</li> <li>Participate in our Employee Share Option Plan (ESOP) for you to be a part of Sonder's success.</li> <li>Salary Packaging and novated leasing</li> <li>Access $250 annually to fund to invest in your wellbeing, empowering you to choose the support that best fits your needs.</li> <li>Free coffee on Tuesdays and catered lunch on Thursdays.</li> <li>Team social fund to connect with your team, plus monthly company wide social events.</li> <li>Dog friendly office.</li> <li>Volunteer leave. 2 days per year to participate in meaningful causes and contribute back to the community.</li> </ul> Check out our life page for more info - Sonder is for Everyone We're committed to building a diverse and inclusive workplace. We encourage applications from people of all backgrounds, experiences, abilities and identities. If you need any support with your application or the recruitment process, please reach out - we'd love to hear from you. Due to the nature of our industry, all Sonder employees are required to complete a National Police Check and Working With Children Check.

Applied Machine Learning Scientist/Engineer - LLMs (Recent PhD Grad)

Ampstek

<div>
 
 Hi Professionals,
 
 
 
 
 
 Greetings From Ampstek!!
 
 
 
 
 
 Hope you are high in your spirits. Please stay safe.
 
 
 
 
 
 Our client is looking for
 
 Applied Scientist
 
 to join a high-growth organization. If you are interested share you resume
 
 sudhakaran.m@ampstek.com
 
 
 
 
 
 
 
 Role: Applied Scientist
 
 
 
 
 Location: Cairo, Egypt(Onsite 5days/Week)
 
 
 
 
 Duration: Contract
 
 
 
 
 
 
 
 Job Description :
 
 
 
 
 
 
 Required skills:
 
 <ul>
 <li>
 2-5 years of experience in developing machine learning models
 </li>
 <li>
 Solid understanding of machine learning concepts and methods
 </li>
 <li>
 Solid data analysis skills to perform statistical analysis and data visualization
 </li>
 <li>
 In-depth experience with natural language processing
 </li>
 <li>
 In-depth experience with distributed big data processing
 </li>
 <li>
 Teamwork and communication skills in an agile development environment
 </li>
 </ul>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Thanks &amp; Regards,
 
 
 
 
 Sudhakaran
 
 
 
 
 IT Recruiter | Europe &amp; UK
 
 
 
 
 Email - sudhakaran.m@ampstek.com
 
 
 
 
 Tel - +44(20)45150009
 
 
 
 
 Ampstek Services Limited
 
 
</div>

Applied Scientist

First Due Solutions

Job Description: Applied ScientistLocation: Bangalore / Hybrid / RemoteCompany: LodgIQIndustry: Hospitality / SaaS / Machine LearningAbout LodgIQHeadquartered in New York, LodgIQ delivers a revolutionary B2B SaaS platform to thetravel industry. By leveraging machine learning and artificial intelligence, we enable preciseforecasting and optimized pricing for hotel revenue management. Backed by HighgateVentures and Trilantic Capital Partners, LodgIQ is a well-funded, high-growth startup with aglobal presence.About the RoleWe are seeking a highly motivated Applied Scientist to join our Data Science team. Thisindividual will play a key role in enhancing and scaling our existing forecasting and pricingsystems and developing new capabilities that support our intelligent decision-makingplatform.We are looking for team members who: &#9679; Are deeply curious and passionate about applying machine learning to real-worldproblems. &#9679; Demonstrate strong ownership and the ability to work independently. &#9679; Excel in both technical execution and collaborative teamwork. &#9679; Have a track record of shipping products in complex environments.What You&rsquo;ll Do &#9679; Build, train, and deploy machine learning and operations research models forforecasting, pricing, and inventory optimization. &#9679; Work with large-scale, noisy, and temporally complex datasets. &#9679; Collaborate cross-functionally with engineering and product teams to move modelsfrom research to production. &#9679; Generate interpretable and trusted outputs to support adoption of AI-driven raterecommendations. &#9679; Contribute to the development of an AI-first platform that redefines hospitality revenuemanagement.Required Qualifications &#9679; Bachelor's or Master&rsquo;s degree or PhD in Computer Science or related field. &#9679; 3-5 years of hands-on experience in a product-centric company, ideally with full modellifecycle exposure.Commented [1]: Leaving note hereAcceptable Degree types - Masters or PhDFieldsOperations ResearchIndustrial/Systems EngineeringComputer ScienceApplied Mathematics&#9679; Demonstrated ability to apply machine learning and optimization techniques to solvereal-world business problems.&#9679; Proficient in Python and machine learning libraries such as PyTorch, statsmodel,LightGBM, scikit-learn, XGBoost&#9679; Strong knowledge of Operations Research models (Stochastic optimization, dynamicprogramming) and forecasting models (time-series and ML-based).&#9679; Understanding of machine learning and deep learning foundations.&#9679; Translate research into commercial solutions&#9679; Strong written and verbal communication skills to explain complex technical conceptsclearly to cross-functional teams.&#9679; Ability to work independently and manage projects end-to-end.Preferred Experience&#9679; Experience in revenue management, pricing systems, or demand forecasting,particularly within the hotel and hospitality domain.&#9679; Applied knowledge of reinforcement learning techniques (e.g., bandits, Q-learning,model-based control).&#9679; Familiarity with causal inference methods (e.g., DAGs, treatment effect estimation).&#9679; Proven experience in collaborative product development environments, working closelywith engineering and product teams.Why LodgIQ?&#9679; Join a fast-growing, mission-driven company transforming the future of hospitality.&#9679; Work on intellectually challenging problems at the intersection of machine learning,decision science, and human behavior.&#9679; Be part of a high-impact, collaborative team with the autonomy to drive initiatives fromideation to production.&#9679; Competitive salary and performance bonuses.&#9679; For more information, visit https://www.lodgiq.comJob Types: Full-time, PermanentPay: &#8377;1,500,000.00 - &#8377;3,000,000.00 per yearApplication Question(s):<ul><li>Last Working Date?</li></ul>Experience:<ul><li>Total Work: 5 years (Preferred)</li><li>Hospitality: 3 years (Preferred)</li></ul>Work Location: Remote

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
The WW DSP Analytics team is a centralized analytics organization within Amazon's Last Mile Delivery Service Partner (DSP) program. We build best-in-class solutions that enable data-driven decision making across our global DSP ecosystem. Our team partners with internal stakeholders, DSP owners, and cross-functional teams to deliver insights that drive operational excellence, business growth, and the success of small business owners in Last Mile delivery. Our work directly impacts customer experience, driver and station associate experience, DSP success, and Amazon's sustainable growth. 
 
We are seeking a passionate Data Scientist with strong machine learning and analytical skills to join our team. You will work on challenging problems in the delivery planning space, applying data science rigor to generate actionable insights that support DSP performance measurement and continuous improvement. 
 
Key job responsibilities 
Develop Science Solutions for DSP Performance: Design and implement data science solutions to optimize Delivery Service Partner (DSP) operations, capacity planning, and performance measurement across the global DSP network 
 
Apply Advanced Machine Learning Techniques: Leverage solid research experience in Machine Learning and statistical modeling to identify opportunities for improving DSP analytics, forecasting models, and performance measurement systems 
 
Optimize DSP Program Policies and Sentiment Risks: Analyze sentiment risks and enhance existing algorithms that support DSP program management, including scorecard metrics, capacity reliability models, and performance evaluation frameworks 
 
Analyze Business Requirements with Return on Investment (ROI) calculation: Demonstrate superior logical thinking by quickly approaching large, ambiguous problems, translating high-level DSP program requirements into mathematical models, and applying models to predict the return on investment. 
 
Build Production-Scale Analytics: Contribute to the development and deployment of scalable data models, dashboards, and automated reporting systems that enable self-service analytics for DSP stakeholders 
 
Accelerate GenAI footprint: Partner with Data Engineers to expand our GenAI tools and improve developer productivity along with raising the bar on data quality. 
 
Conduct Independent Data Analysis: Mine and analyze complex datasets across multiple domains (performance metrics, financial data, operational data) using programming and statistical analysis tools to generate actionable insights 
 
Thrive in a Collaborative Environment: Excel in a fast-paced analytics organization that encourages collaborative and creative problem-solving, measure and communicate analytical risks, constructively critique peer work, and align research focuses with DSP program strategic needs 
 
Partner Cross-Functionally: Work closely with Business Intelligence Engineers, program teams, and DSP stakeholders to define KPIs, validate analytical approaches, and ensure insights drive meaningful business outcomes<h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>2+ years of data scientist experience</li><li>3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience</li><li>3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience</li><li>1+ years of guiding and coaching a group of researchers experience</li><li>1+ years of working with or evaluating AI systems experience</li><li>1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience</li><li>Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)</li><li>Experience applying theoretical models in an applied environment</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)</li><li>Knowledge of machine learning concepts and their application to reasoning and problem-solving</li><li>Experience in Python, Perl, or another scripting language</li><li>Experience in a ML or data scientist role with a large technology company</li><li>Experience in defining and creating benchmarks for assessing GenAI model performance</li><li>Experience working on multi-team, cross-disciplinary projects</li><li>Experience applying quantitative analysis to solve business problems and making data-driven business decisions</li><li>Experience effectively communicating complex concepts through written and verbal communication</li></ul> 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.</div>

Data Scientist, WW DSP Analytics

Atlassian

<div>Overview:

Working at Atlassian
Atlassians can choose where they work &ndash; whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. This is a remote position. To help our teams work together effectively, this role requires you to be located in India.
Atlassian is looking for a Principal Machine Learning Scientist to join our Central AI team. The Central AI organisation constructs the fundamental infrastructure, data pipeline, frameworks, models, and other capabilities to expedite AI feature development throughout the entire company.
Central AI org
The Central AI org is part of the larger Atlassian Intelligence program. Its purpose is to accelerate AI innovation across all our products and platform, provide cohesive AI experiences and setup up an Atlassian AI infrastructure for the future.
While it's anticipated that the majority of AI-driven initiatives will be developed and executed by federated product teams within Atlassian, the role of Central AI is pivotal to this process. Central AI is tasked with constructing the underlying infrastructure and capacities, which are crucial for the seamless integration and optimal functionality of AI across various departments. By doing so, Central AI ensures that different teams within the organisation do not work in silos but have access to a unified foundation that promotes efficiency and collaboration. Additionally, Central AI is responsible for developing some of the core shared experiences typical in the AI domain, such as search, knowledge discovery and conversation.
Your future team
To become a 100-year company, we need a world-class engineering organisation made up of empowered teams who have the tools and infrastructure to do the best work of their careers.
As part of a unified R&amp;D team, Engineering is prioritising key initiatives which support our customers in moving to cloud while simultaneously continuing to bring the most value to our customers through investments across our core product suite &ndash; including Jira, Confluence, Trello, and Bitbucket.
We're looking for people who want to write the future and who believe that we can accomplish so much more together.
Responsibilities:

What you&rsquo;ll do
As a Principal Machine Learning engineer, you will drive the development and implementation of the cutting edge machine learning algorithms, training sophisticated models, collaborating with product, engineering, and analytics teams, to build the AI functionalities into each Atlassian products and services. Your daily responsibilities will encompass a broad spectrum of tasks such as designing system and model architectures, conducting rigorous experimentation and model evaluations, and providing guidance to emerging ML engineers. Your role is pivotal, stretching beyond these tasks, ensuring AI's transformative potential is realised across our offerings.
Qualifications:

On the first day, we'll expect you to have<ul><li>
Bachelor's or Master's degree (preferably a Computer Science degree or equivalent experience)</li><li>
10+ years of related industry experience in the data science domain</li><li>
Expertise in Python or Java with and the ability to write performant production-quality code, familiarity with SQL, knowledge of Spark and cloud data environments (e.g. AWS, Databricks)</li><li>
Experience building and scaling machine learning models in business applications using large amounts of data</li><li>
Explain data science concepts to diverse audiences, create a compelling story</li><li>
Focus on business practicality and the 80/20 rule; very high bar for output quality, but recognize the business benefit of &quot;having something now&quot; vs &quot;perfection sometime in the future&quot;</li><li>
Agile development mindset, appreciating the benefit of constant iteration and improvement</li></ul>
It's great, but not required, if you have<ul><li>
Experience working in a consumer or B2C space for a SaaS product provider, or the enterprise/B2B space</li><li>
Experience developing deep learning-based models and working on LLM-related applications</li><li>
Excel in solving ambiguous and complex problems, being able to navigate through uncertain situations, breaking down complex challenges into manageable components and developing innovative solutions.</li></ul>
Our perks &amp; benefits
Atlassian offers a variety of perks and benefits to support you, your family and to help you engage with your local community. Our offerings include health coverage, paid volunteer days, wellness resources, and so much more. Visit go.atlassian.com/perksandbenefits to learn more.
About Atlassian
At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together.
We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.
To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
To learn more about our culture and hiring process, visit go.atlassian</div>

Principal Machine Learning Engineer

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