410 lines
31 KiB
HTML
410 lines
31 KiB
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<title>AI/ML Platform Architect - JOB-46300 | LRS® Careers</title>
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"description": "<p>LRS Consulting Services is seeking an AI/ML Platform Engineer for an exciting contract to hire opportunity with our client. </p>
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<p dir="ltr"><strong>AI/ML Platform Engineer</strong></p>
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<p dir="ltr">Remote (100%) | Contract-to-Hire</p>
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<p dir="ltr"><strong>Position Summary</strong></p>
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<p dir="ltr">LRS Consulting Services is seeking an AI/ML Platform Engineer to join a growing cybersecurity startup building an AI-powered platform that correlates posture and risk data across Identity, Device, Network, Application, and Data environments. This platform delivers a unified view of security risk and powers Zero Trust decision-making for enterprise customers.</p>
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<p dir="ltr">This is a builder's role. We need someone who has actually built or trained a model or AI-driven tool, designed it, tuned it, shipped it, not someone who has primarily customized or prompted publicly available models on behalf of a large organization. If you can talk in specifics about the models you've built, the features you engineered, and how you tuned and evaluated them, we want to talk to you.</p>
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<p dir="ltr"><strong>What You Will Do</strong></p>
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<ul dir="ltr">
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<li>Design, build, and tune machine learning models (e.g., risk scoring, anomaly detection) that power the platform's security posture analysis</li>
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<li>Build on and improve the LLM-based layer that correlates and clusters posture/risk data and turns it into clear, human-readable analysis</li>
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<li>Get hands-on with the full lifecycle: data pipelines, feature engineering, model tuning and evaluation, and deployment</li>
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<li>Take ownership of pieces of the AI platform end-to-end and help decide how they should evolve</li>
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<li>Work closely with product, engineering, and customer success to ship AI capabilities that make security posture data genuinely useful to customers</li>
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<li>Evaluate and bring in new AI/ML techniques as the platform and the space evolve</li>
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<li>Grow into greater architectural ownership and strategic direction over time. You won't be expected to own that on day one, but the path is real for the right person</li>
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</ul>
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<p dir="ltr"><strong>Required Qualifications</strong></p>
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<ul dir="ltr">
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<li>Hands-on experience building, training, or fine-tuning machine learning models for a specific purpose (e.g., risk scoring, anomaly detection, classification, clustering). We need someone who has designed, tuned, and shipped a model or AI-driven tool, not someone who has primarily customized or prompted publicly available models on behalf of a large organization</li>
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<li>Experience with the full ML lifecycle end-to-end: data pipelines, feature engineering, model training, evaluation, tuning, and deployment. You should be comfortable owning the entire process rather than handing pieces off</li>
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<li>Working experience with LLMs beyond basic prompting, including correlation, clustering, interpretation workflows, or building LLM-based layers that transform raw data into human-readable analysis</li>
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<li>Proficiency in Python with hands-on depth in ML frameworks such as PyTorch, TensorFlow, or scikit-learn</li>
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<li>Experience deploying and iterating on AI/ML solutions in AWS (or a comparable cloud stack)</li>
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<li>Ability to speak in specifics about models you've built: why you chose a particular architecture, how you engineered features, how you evaluated and tuned performance, and what you would do differently</li>
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<li>Comfort taking end-to-end ownership of AI platform components and making decisions about how they should evolve</li>
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<li>A startup mindset: energized by ambiguity, comfortable wearing multiple hats, and able to move fast in a small, less structured team where you won't have a team doing the work for you</li>
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<li>Strong communication skills with the ability to work directly with product, engineering, customer success, and leadership</li>
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<li>Bachelor's or Master's in Computer Science, AI/ML, or a related field, or equivalent hands-on experience</li>
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<li><strong>All candidates must reside in the United States. </strong></li>
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<li><strong>Candidates must have permanent authorization to work in the United States without sponsorship. </strong></li>
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<li><strong>Temporary visa candidates will not be considered. </strong></li>
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<li><strong>Third-party candidates will not be considered for this position.</strong></li>
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</ul>
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<p dir="ltr"><strong>Preferred Qualifications</strong></p>
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<ul dir="ltr">
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<li>Familiarity with cybersecurity, cloud security, identity, or security posture management</li>
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<li>Experience with LLM-based clustering, retrieval, or interpretation workflows</li>
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<li>Prior experience at a startup or in a small, high-ownership team environment</li>
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</ul>
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<p dir="ltr">The base range for this contract position is $85 - $110 per hour, depending on experience.</p>
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<p dir="ltr">Our pay ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hires of this position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.</p>
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<p dir="ltr">LRS is an equal opportunity employer. Applicants for employment will receive consideration without unlawful discrimination based on race, color, religion, creed, national origin, sex, age, disability, marital status, gender identity, domestic partner status, sexual orientation, genetic information, citizenship, status or protected veteran status.</p>
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<p dir="ltr">In some cases, LRS Consulting uses generative artificial intelligence ("AI") in support of our hiring processes. LRS takes steps to ensure the use of AI does not result in discrimination based on protected class(es). AI may be used in the hiring process solely in support of the assessment of candidate qualifications. All decisions in the hiring process are made by LRS employees. If AI will be used in the hiring process for the position for which you are applying, you will be notified and will have the opportunity to opt out. Please contact <a href="mailto:AI.Questions@lrs.com" target="_blank" rel="noopener">AI.Questions@lrs.com</a> with any questions.</p>",
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<span class="card-date">
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Added Sep 08, 2026
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</span>
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<span class="card-title-category">
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<span class="card-title">AI/ML Platform Architect</span>
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<span class="card-title">(46300)</span>
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<span class="card-category"></span>
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</span>
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<span class="card-location">
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Remote, Remote
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</span>
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<span class="card-separator">|</span>
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<span class="card-type">
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Temp to Perm
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</span>
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<a class="apply" target="_blank" href="https://evoportalus.tracker-rms.com/LRS/apply?jobcode=46300">Apply</a>
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<p>For additional information on how we handle your data, see <a href="https://www.LRS.com/privacy" target="_blank">www.LRS.com/privacy</a></p>
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<a href="https://www.lrs.com/Resources/e208f9da-62fc-4f63-8411-02d686e8f2c2/LRS" title="View Unlocking the Benefit of Joining the LRS Team" target="_blank" class="benefits-link">
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<h4>What to do if you suspect fraud:</h4>
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<p>If you receive a suspicious offer or communication claiming to be from us, do not share any personal or financial information. You can notify us using our contact page at <a href="https://www.lrs.com/contact/">Contact Levi, Ray & Shoup, Inc</a>.</p>
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<h4>IMPORTANT NOTES:</h4>
|
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<ul>
|
||
<li>All legitimate correspondence from our recruiting team will only come from an email address ending in @lrs.com. We do not use generic domains like @gmail.com, @yahoo.com, or @outlook.com.</li>
|
||
<li>We <strong>never</strong> conduct interviews solely via text-based chat on Microsoft Teams, Telegram, or WhatsApp. All virtual interviews involve a scheduled video or phone call with a member of our team.</li>
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<li>LRS will <strong>never</strong> ask a candidate for payment, fees, or to purchase equipment (e.g., laptops, software) as a condition of employment.</li>
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<li>All genuine job opportunities are listed directly on our official careers portal at <a href="https://jobs.lrs.com/">Careers</a>.</li>
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</ul>
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<div class="job-heading">
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<span class="fill"></span>
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<div class="job-actions">
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</div>
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<h2>Job Description</h2>
|
||
</div>
|
||
<div class="job-details">
|
||
<p>LRS Consulting Services is seeking an AI/ML Platform Engineer for an exciting contract to hire opportunity with our client. </p>
|
||
<p dir="ltr"><strong>AI/ML Platform Engineer</strong></p>
|
||
<p dir="ltr">Remote (100%) | Contract-to-Hire</p>
|
||
<p dir="ltr"><strong>Position Summary</strong></p>
|
||
<p dir="ltr">LRS Consulting Services is seeking an AI/ML Platform Engineer to join a growing cybersecurity startup building an AI-powered platform that correlates posture and risk data across Identity, Device, Network, Application, and Data environments. This platform delivers a unified view of security risk and powers Zero Trust decision-making for enterprise customers.</p>
|
||
<p dir="ltr">This is a builder's role. We need someone who has actually built or trained a model or AI-driven tool, designed it, tuned it, shipped it, not someone who has primarily customized or prompted publicly available models on behalf of a large organization. If you can talk in specifics about the models you've built, the features you engineered, and how you tuned and evaluated them, we want to talk to you.</p>
|
||
<p dir="ltr"><strong>What You Will Do</strong></p>
|
||
<ul dir="ltr">
|
||
<li>Design, build, and tune machine learning models (e.g., risk scoring, anomaly detection) that power the platform's security posture analysis</li>
|
||
<li>Build on and improve the LLM-based layer that correlates and clusters posture/risk data and turns it into clear, human-readable analysis</li>
|
||
<li>Get hands-on with the full lifecycle: data pipelines, feature engineering, model tuning and evaluation, and deployment</li>
|
||
<li>Take ownership of pieces of the AI platform end-to-end and help decide how they should evolve</li>
|
||
<li>Work closely with product, engineering, and customer success to ship AI capabilities that make security posture data genuinely useful to customers</li>
|
||
<li>Evaluate and bring in new AI/ML techniques as the platform and the space evolve</li>
|
||
<li>Grow into greater architectural ownership and strategic direction over time. You won't be expected to own that on day one, but the path is real for the right person</li>
|
||
</ul>
|
||
<p dir="ltr"><strong>Required Qualifications</strong></p>
|
||
<ul dir="ltr">
|
||
<li>Hands-on experience building, training, or fine-tuning machine learning models for a specific purpose (e.g., risk scoring, anomaly detection, classification, clustering). We need someone who has designed, tuned, and shipped a model or AI-driven tool, not someone who has primarily customized or prompted publicly available models on behalf of a large organization</li>
|
||
<li>Experience with the full ML lifecycle end-to-end: data pipelines, feature engineering, model training, evaluation, tuning, and deployment. You should be comfortable owning the entire process rather than handing pieces off</li>
|
||
<li>Working experience with LLMs beyond basic prompting, including correlation, clustering, interpretation workflows, or building LLM-based layers that transform raw data into human-readable analysis</li>
|
||
<li>Proficiency in Python with hands-on depth in ML frameworks such as PyTorch, TensorFlow, or scikit-learn</li>
|
||
<li>Experience deploying and iterating on AI/ML solutions in AWS (or a comparable cloud stack)</li>
|
||
<li>Ability to speak in specifics about models you've built: why you chose a particular architecture, how you engineered features, how you evaluated and tuned performance, and what you would do differently</li>
|
||
<li>Comfort taking end-to-end ownership of AI platform components and making decisions about how they should evolve</li>
|
||
<li>A startup mindset: energized by ambiguity, comfortable wearing multiple hats, and able to move fast in a small, less structured team where you won't have a team doing the work for you</li>
|
||
<li>Strong communication skills with the ability to work directly with product, engineering, customer success, and leadership</li>
|
||
<li>Bachelor's or Master's in Computer Science, AI/ML, or a related field, or equivalent hands-on experience</li>
|
||
<li><strong>All candidates must reside in the United States. </strong></li>
|
||
<li><strong>Candidates must have permanent authorization to work in the United States without sponsorship. </strong></li>
|
||
<li><strong>Temporary visa candidates will not be considered. </strong></li>
|
||
<li><strong>Third-party candidates will not be considered for this position.</strong></li>
|
||
</ul>
|
||
<p dir="ltr"><strong>Preferred Qualifications</strong></p>
|
||
<ul dir="ltr">
|
||
<li>Familiarity with cybersecurity, cloud security, identity, or security posture management</li>
|
||
<li>Experience with LLM-based clustering, retrieval, or interpretation workflows</li>
|
||
<li>Prior experience at a startup or in a small, high-ownership team environment</li>
|
||
</ul>
|
||
<p dir="ltr">The base range for this contract position is $85 - $110 per hour, depending on experience.</p>
|
||
<p dir="ltr">Our pay ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hires of this position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.</p>
|
||
<p dir="ltr">LRS is an equal opportunity employer. Applicants for employment will receive consideration without unlawful discrimination based on race, color, religion, creed, national origin, sex, age, disability, marital status, gender identity, domestic partner status, sexual orientation, genetic information, citizenship, status or protected veteran status.</p>
|
||
<p dir="ltr">In some cases, LRS Consulting uses generative artificial intelligence ("AI") in support of our hiring processes. LRS takes steps to ensure the use of AI does not result in discrimination based on protected class(es). AI may be used in the hiring process solely in support of the assessment of candidate qualifications. All decisions in the hiring process are made by LRS employees. If AI will be used in the hiring process for the position for which you are applying, you will be notified and will have the opportunity to opt out. Please contact <a href="mailto:AI.Questions@lrs.com" target="_blank" rel="noopener">AI.Questions@lrs.com</a> with any questions.</p>
|
||
<p style="font-size: .80em; line-height: 1.15;">
|
||
Colorado Pay Range:<br />
|
||
80.00 - 100.00/per Hour
|
||
</p>
|
||
</div>
|
||
<div class="notice-fraud">
|
||
<h4>What to do if you suspect fraud:</h4>
|
||
<p>If you receive a suspicious offer or communication claiming to be from us, do not share any personal or financial information. You can notify us using our contact page at <a href="https://www.lrs.com/contact/">Contact Levi, Ray & Shoup, Inc</a>.</p>
|
||
<h4>IMPORTANT NOTES:</h4>
|
||
<ul>
|
||
<li>All legitimate correspondence from our recruiting team will only come from an email address ending in @lrs.com. We do not use generic domains like @gmail.com, @yahoo.com, or @outlook.com.</li>
|
||
<li>We <strong>never</strong> conduct interviews solely via text-based chat on Microsoft Teams, Telegram, or WhatsApp. All virtual interviews involve a scheduled video or phone call with a member of our team.</li>
|
||
<li>LRS will <strong>never</strong> ask a candidate for payment, fees, or to purchase equipment (e.g., laptops, software) as a condition of employment.</li>
|
||
<li>All genuine job opportunities are listed directly on our official careers portal at <a href="https://jobs.lrs.com/">Careers</a>.</li>
|
||
</ul>
|
||
</div>
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