machine learning lead

Agile Defense

<div><div><b>About Agile Defense</b></div>
<div></div>
<div>At Agile Defense we know that action defines the outcome and new challenges require new solutions. That&rsquo;s why we always look to the future and embrace change with an unmovable spirit and the courage to build for what comes next.</div>
<div></div>
<div>Our vision is to bring adaptive innovation to support our nation's most important missions through the seamless integration of advanced technologies, elite minds, and unparalleled agility&mdash;leveraging a foundation of speed, flexibility, and ingenuity to strengthen and protect our nation&rsquo;s vital interests.</div><div></div><div><br>
<div><b>
Requisition #: </b>1706</div>
<div><b>Job Title:</b> Data Science &amp; Analytics Technical Lead</div>
<div><b>Location:</b> Tampa, FL</div>
<div><b>Clearance Level: </b>Top Secret / SCI, Must Have Clearance to Start</div>
</div><h3 class="jobSectionHeader"><b>Job Description</b></h3><ul>
<li>Lead the design, development, and deployment of complex machine learning models, statistical analysis, and data mining techniques to solve advanced business problems.</li>
<li>Build and improve predictive models for customer behavior, churn prediction, demand forecasting, and other business-critical areas.</li>
<li>Conduct advanced exploratory data analysis (EDA) to uncover trends, patterns, and actionable insights from structured and unstructured data sources.</li>
<li>Develop and implement algorithms for classification, regression, clustering, natural language processing (NLP), and recommendation systems.</li>
<li>Collaborate closely with cross-functional teams, including data engineering, product, and business teams, to define data science objectives and translate them into actionable projects. Communicate technical results, findings, and recommendations to stakeholders at all levels, ensuring data-driven strategies are clearly understood and actionable.</li>
<li>Lead efforts in feature engineering, hyperparameter tuning, and model validation to ensure high model accuracy, performance, and robustness. Evaluate and apply cutting-edge machine learning frameworks, tools, and techniques to optimize workflows and drive innovation.</li>
<li>Mentor junior data scientists, providing technical guidance and promoting best practices in data science and machine learning.</li>
<li>Work with data engineers to ensure clean, accurate, and accessible data pipelines, ensuring efficient deployment of data products and models.</li>
</ul><h3 class="jobSectionHeader"><b>Education and Background</b></h3><ul>
<li>Typically has a Bachelor's degree in Data Science, Computer Science, Mathematics, Statistics, or a related field (masters degree or PhD strongly preferred)., and 5+ years of experience in data science, machine learning, or a related role, with a track record of leading successful data science projects., or equivalent relevant work experience; e.g., each year of work experience may be substituted for each year of education required.</li>
</ul><h3 class="jobSectionHeader"><b>Years of Experience</b></h3><div>
5+ years</div><h3 class="jobSectionHeader"><b>
Required Skills</b></h3><ul>
<li>The contractor shall identify a Data Science &amp; Analytics Technical Lead by name who shall drive the strategic integration of advanced analytics capabilities across the SOF enterprise. This leadership role is centered on applying scientific methods, algorithms, and systems to transform vast quantities of both structured and unstructured data into actionalble insights and essential knowledge for the Head Quarters (HQ) Staff, Service Components, and TSOCs. Have active active TS/SCI clearance</li>
</ul><h3 class="jobSectionHeader"><b>Preferred Skills</b></h3><ul>
<li>Five years of experience working in SOF analytical support</li>
<li>Three years experience centrally managing distributed data support teams in SOF organizations HQ echelon</li>
<li>Three years experience with SOF digital capabilities</li>
<li>Three years experience with SOF HQ elements, SOF Service Components HQs, and SOF Theater Special Operations Command</li>
</ul><h3 class="jobSectionHeader"><b>Working Conditions</b></h3><div>
General Office Environment</div><div><b>
Our Core Values</b></div>
<div></div>
<div>Employees of Agile Defense are our number one priority, and the importance we place on our culture here is fundamental. Our culture is alive and evolving, but it always stays true to its roots. Here, you are valued as a family member, and we believe that we can accomplish great things together. Agile Defense has been highly successful in the past few years due to our employees and the culture we create together.</div>
<div></div>
<div>What makes us Agile? We call it the 6Hs, the values that define our culture and guide everything we do. Together, these values infuse vibrancy, integrity, and a tireless work ethic into advancing the most important national security and critical civilian missions. It's how we show up every day. It's who we are.</div>
<div></div>
<ul><li><b>Happy </b>- Be Infectious. Happiness multiplies and creates a positive and connected environment where motivation and satisfaction have an outsized effect on everything we do.</li>
<li><b>Helpful</b> - Be Supportive. Being helpful is the foundation of teamwork, resulting in a supportive atmosphere where collaboration flourishes, and collective success is celebrated.</li>
<li><b>Honest</b> - Be Trustworthy. Honesty serves as our compass, ensuring transparent communication and ethical conduct, essential to who we are and the complex domains we support.</li>
<li><b>Humble</b> - Be Grounded. Success is not achieved alone, humility ensures a culture of mutual respect, encouraging open communication, and a willingness to learn from one another and take on any task.</li>
<li><b>Hungry </b>- Be Eager. Our hunger for excellence drives an insatiable appetite for innovation and continuous improvement, propelling us forward in the face of new and unprecedented challenges.</li>
<li><b>Hustle</b> - Be Driven. Hustle is reflected in our relentless work ethic, where we are each committed to going above and beyond to advance the mission and achieve success.</li>
</ul>
<div></div><div><b>Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities</b></div>
<p>
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.</p></div>

Data Science & Analytics Technical Lead

Raytheon

<div><p><b>Date Posted:</b></p>
2026-06-30<p><b>
Country:</b></p>
United Kingdom<p><b>
Location:</b></p>
Warminster, Wiltshire<p><b>
Position Role Type:</b></p>
Hybrid<p></p><p><b>
Job Title: </b>Ai Solutions Lead</p><p><b>
Function:</b> Engineering</p><p><b>
Duration: </b>Permanent</p><p><b>
Hours</b>: Full Time (37 hours per week)</p><p><b>
Location(s):</b> Warminster</p><p></p><p><b>
Security Clearance Requirements:</b> SC &ndash; Must be eligible to work in the UK without sponsorship.
</p><p></p><p><b>Why join Raytheon
</b></p><p></p><p>Raytheon UK is a powerhouse in defence and aerospace, where innovation meets impact. As a key partner to the UK government and global customers, we tackle the toughest challenges across land, sea, air, space, and cyberspace. Beyond cutting-edge defence solutions, we lead the way in digital training transformation for both military and commercial clients. At Raytheon UK, you will work with pioneering technology, collaborate with top industry experts, and be part of a dynamic team that fuels your growth. Whether you're looking to push boundaries, develop your skills, or make a real-world impact, your future starts here.</p><p></p><p><b>
The role:</b></p><p></p><p><br>
This is more than a job &mdash; <b>it&rsquo;s a mission</b>. You will be part of a high-impact, collaborative environment, where we expect everyone to live the values and standards of the British Army. Every person in our team plays a critical role in delivering OMNIA&rsquo;s vision; designing, delivering, and transforming collective training so the British Army is ready to fight and win.</p><p>
You&rsquo;ll work in a matrix organisation and report operationally through OMNIA Training and functionally to the Enterprise Architect. Ultimately, you&rsquo;ll work for the British Army, championing innovation, and helping shape the future of military collective training.</p><p></p><p><b>
Key Responsibilities:</b></p><p></p><ul><li><p>
Lead the design and delivery of end-to-end AI/ML solutions aligned to organisational strategy and operational objectives.</p></li><li><p>
Define scalable, secure, and maintainable AI architectures, covering data pipelines, model lifecycle management, deployment, and monitoring.</p></li><li><p>
Establish architectural standards, design patterns, and engineering best practices.</p></li><li><p>
Provide technical oversight across the full AI lifecycle: concept, prototyping, production deployment, and optimisation.</p></li><li><p>
Review and approve solution designs produced by AI Solution Engineers and wider delivery teams.</p></li><li><p>
Lead, mentor, and develop AI Solution Engineer(s) and associated technical staff.</p></li><li><p>
Set technical direction and ensure consistency in engineering standards across AI initiatives.</p></li><li><p>
Conduct code and design reviews to ensure quality, security, and maintainability.</p></li><li><p>
Identify capability gaps and drive upskilling across the AI team.</p></li><li><p>
Foster a collaborative, high-performance engineering culture.</p></li><li><p>
Own technical delivery of AI solutions, ensuring alignment with scope, timelines, and quality expectations.</p></li><li><p>
Oversee deployment of AI systems into secure or controlled environments.</p></li><li><p>
Ensure compatibility of AI solutions with DevSecOps pipelines and enterprise technology stacks.</p></li><li><p>
Define and monitor performance metrics for deployed models, ensuring operational effectiveness and reliability.</p></li><li><p>
Lead remediation and optimisation efforts when performance, compliance, or operational risks arise.</p></li><li><p>
Embed ethical AI principles, including fairness, explainability, auditability, and transparency, into solution design.</p></li><li><p>
Ensure compliance with data governance, security, and regulatory requirements.</p></li><li><p>
Support accreditation and assurance activities within regulated or defence environments.</p></li><li><p>
Identify, assess, and mitigate technical risks associated with AI deployment.</p></li><li><p>
Translate operational or business requirements into AI-enabled solution approaches.</p></li><li><p>
Engage senior stakeholders, providing clear technical briefings and strategic recommendations.</p></li><li><p>
Contribute to AI capability roadmaps and innovation strategies.</p></li><li><p>
Lead technical input into bids, proposals, or programme planning activities where required.</p></li><li><p>
Conduct horizon scanning to evaluate emerging AI technologies and assess relevance to operational use cases.</p></li><li><p>
Drive continuous improvement of AI engineering practices, tooling, and delivery methods.</p></li><li><p>
Champion adoption of MLOps practices to enhance repeatability, traceability, and scalability.</p></li><li><p>
Promote knowledge sharing and best practice dissemination across engineering teams.</p></li></ul><p></p><p><b>
Who we are looking for:</b></p><p></p><p>
You&rsquo;ll have a mission focus, and the enthusiasm and drive to &lsquo;get things done&rsquo;. You&rsquo;ll want to work in collaboration with other defence training organisations, and the British Army. You won&rsquo;t let bureaucracy get in the way of what needs to be done, you&rsquo;ll learn lessons and share these lessons across the team. You&rsquo;ll understand what it means to put the mission first.</p><p>
The successful candidate will be a technically astute AI Solution Lead who thrives on engineering execution to realise enterprise goals. You will be responsible for designing and sustaining AI/ML solutions that align with the Army Collective Training Service (ACTS) architectural vision. The AI Solution Lead must possess a deep understanding of AI technologies, with the ability to leverage data insights for model development and optimisation using frameworks such as TensorFlow and PyTorch, while also driving intelligent process automation across the machine learning lifecycle through platforms like Azure Machine Learning. This role is pivotal in aligning AI technology with architecture vision and goals, ensuring secure, interoperable systems to drive and automate data driven decision making.</p><p></p><p><b>
Essential Skills and Experience:</b></p><p></p><ul><li><p>
Extensive experience in leading technical teams designing and delivering end-to-end AI/ML solutions from concept to production within regulated or controlled environments.</p></li><li><p>
Strong Python expertise and deep knowledge of ML frameworks</p></li><li><p>
Experience defining scalable ML architectures, including lifecycle management, monitoring, and resilience strategies</p></li><li><p>
Experience overseeing deployment using containerisation and orchestration platforms and governing CI/CD and MLOps practices</p></li><li><p>
Strong understanding of API-led integration within enterprise systems</p></li><li><p>
Experience embedding responsible AI principles into architectural design</p></li><li><p>
Strong understanding of secure coding, data protection, and governance frameworks, and experience supporting accreditation or assurance processes</p></li><li><p>
Accountability for technical risk identification and mitigation</p></li><li><p>
Experience translating operational requirements into AI-enabled capabilities</p></li><li><p>
Ability to engage and influence senior stakeholders</p></li><li><p>
Experience defining AI roadmaps and technical strategy</p></li><li><p>
Strong decision-making capability balancing innovation, risk, and operational constraints</p></li><li><p>
Proven experience leading, mentoring, and developing AI/ML engineers</p></li><li><p>
Strong systems-level analytical thinking</p></li><li><p>
Ability to operate autonomously with accountability for outcomes</p></li><li><p>
Degree in relevant discipline or equivalent senior-level experience</p></li></ul><p></p><p><b>
What we offer:
</b></p><p></p><ul><li><p>Competitive salaries.</p></li><li><p>
25 days holiday + statutory public holidays, plus opportunity to buy and sell up to 5 days (37hr)</p></li><li><p>
Contributory Pension Scheme (up to 10.5% company contribution)</p></li><li><p>
Company bonus scheme (discretionary).</p></li><li><p>
6 times salary &lsquo;Life Assurance&rsquo; with pension.</p></li><li><p>
Flexible Benefits scheme with extensive salary sacrifice schemes, including Health Cashplan, Dental, and Cycle to Work amongst others.</p></li><li><p>
Enhanced sick pay.</p></li><li><p>
Enhanced family friendly policies including enhanced maternity, paternity &amp; shared parental leave</p></li></ul><p></p><p><b>
Work Culture</b></p><p></p><ul><li><p>
37hr working week, although hours may vary depending on role, job requirement or site-specific arrangements.</p></li><li><p>
Remote, hybrid and site based working opportunities, dependant on your needs and the requirements of the role.</p></li><li><p>
A grownup flexible working culture that is output, not time spent at desk, focussed. More formal flexible working arrangements can also be requested and assessed subject to the role. Please enquire or highlight any request to our Talent Acquisition team to explore the flexible working possibilities.</p></li><li><p>
Up to 5 paid days volunteering each year</p></li></ul><p></p><p><b>
For this role the successful hire will need to be a permanent UK resident and be eligible to for and hold an SC security and background check.</b></p><p></p><p><b>
RTX
</b></p><p></p><p>Raytheon UK is a landed company and part of the wider RTX organisation. Headquartered in Arlington, Virginia, USA, but with over 180,000 employees globally across every continent, RTX provides advanced systems and services for commercial, military and government customers worldwide and comprises three industry-leading businesses &ndash; Collins Aerospace Systems, Pratt &amp; Whitney, and Raytheon.
</p><p></p><p>Supporting over 35,000 jobs across 13 UK sites, RTX is helping to drive prosperity. Each year our work contributes over &pound;2.7bn to the UK economy and offers a wealth of opportunities to 4,000 suppliers across England, Scotland, Wales and Northern Ireland. We&rsquo;re investing in all corners of the country, supporting 29,040 jobs in England, 3,040 in Northern Ireland, 1,900 in Scotland and 1,600 in Wales.</p><p>
#LI-AS3</p><p></p><p><i>
RTX adheres to the principles of equal employment. All qualified applications will be given careful consideration without regard to ethnicity, color, religion, gender, sexual orientation or identity, national origin, age, disability, protected veteran status or any other characteristic protected by law.</i>
</p><p></p><p><b>Privacy Policy and Terms:</b></p></div><p></p>

AI Solution Lead

Kasmoprav

<p>We are looking for an experienced AI Lead to spearhead the AI engineering track for an enterprise-grade Agent Development Platform (ADP). This is a hands-on leadership role responsible for architecting, building, and scaling AI-powered agent frameworks and platforms.</p><p>Key Responsibilities:</p><ul><li>Lead the design and development of AI agent frameworks and multi-agent systems.</li><li>Define AI architecture, evaluation strategies, and AI security standards.</li><li>Build production-grade LLM applications, RAG systems, and AI agents.</li><li>Drive model selection, orchestration, memory management, and observability.</li><li>Lead and mentor a team of AI engineers and establish engineering best practices.</li><li>Collaborate with client stakeholders and act as the technical leader for AI initiatives.</li></ul><p>Required Skills:</p><ul><li>12+ years of software/AI engineering experience with 3+ years in LLM-powered systems.</li><li>Expert-level Python programming.</li><li>Hands-on experience with LangGraph, Claude Agent SDK, LangChain, and LangSmith.</li><li>Strong experience with RAG, AI agents, multi-agent systems, and LLMOps.</li><li>Experience with Neo4j, PGVector, LiteLLM, Langfuse, AWS Bedrock, and distributed systems.</li><li>Strong understanding of AI security, prompt injection defense, and evaluation frameworks.</li><li>Experience leading engineering teams and client-facing technical discussions.</li></ul><p>Good to Have:</p><ul><li>Experience in Commercial Real Estate, Legal, Insurance, or Financial Services domains.</li><li>Experience with SOC2, GDPR, and platform productization.</li></ul><p>Pay: ₹500,000.00 - ₹900,000.00 per year</p><p>Benefits:</p><ul><li>Health insurance</li><li>Life insurance</li><li>Work from home</li></ul><p>Work Location: Hybrid remote in Pune, Maharashtra</p>

AI Lead(Tango Project)

MYLO

<div>Role Overview<p>
We are seeking an experienced <b>Engineering Manager &ndash; Data Science</b> to lead a high-performing Data Science squad responsible for delivering scalable machine learning solutions, predictive models, and AI-driven products that drive business impact.</p><p></p><p>
The ideal candidate combines deep technical expertise in Data Science and Machine Learning with strong people leadership capabilities. This role requires a strategic thinker who can manage a multidisciplinary squad, define technical roadmaps, mentor engineers and data scientists, and collaborate closely with Product, Engineering, Analytics, and Business stakeholders.</p><p></p>
Key ResponsibilitiesLeadership &amp; Team Management<ul><li>
Lead, coach, and develop a squad of Data Scientists, Machine Learning Engineers.</li><li>
Drive team performance through goal setting, mentoring, career development, and continuous feedback.</li><li>
Build and foster a culture of innovation, ownership, collaboration, and technical excellence.</li><li>
Support recruitment, onboarding, and talent development initiatives.</li><li>
Manage squad capacity, planning, and execution to ensure successful delivery of strategic projects.</li></ul>
Technical Leadership<ul><li>
Define and execute the Data Science roadmap aligned with business objectives.</li><li>
Lead the design, development, deployment, and monitoring of machine learning models and AI solutions.</li><li>
Establish engineering best practices for model development, experimentation, MLOps, and production deployment.</li><li>
Guide architectural decisions related to data platforms, machine learning infrastructure, and AI systems.</li><li>
Ensure scalability, reliability, and maintainability of Data Science solutions.</li></ul>
Stakeholder Management<ul><li>
Partner with Product Managers, Engineering Leaders, and Business stakeholders to identify opportunities for data-driven decision making.</li><li>
Translate complex business problems into analytical and machine learning solutions.</li><li>
Communicate technical findings and recommendations to both technical and non-technical audiences.</li><li>
Drive alignment across cross-functional teams to deliver measurable business outcomes.</li></ul>
Delivery &amp; Execution<ul><li>
Oversee end-to-end project delivery from discovery and experimentation to production deployment.</li><li>
Monitor KPIs and model performance to ensure continuous improvement.</li><li>
Balance technical debt, innovation, and business priorities effectively.</li><li>
Drive agile delivery practices within the squad.</li></ul><br>
<b>
Requirements</b><br>
<ul><li><b>
10+ years of experience</b> in Data Science, Machine Learning, Software Engineering, or related technical fields.</li><li><b>
4+ years of people management experience</b> leading Data Science or Machine Learning teams.</li><li>
Proven experience leading cross-functional squads in product-driven environments.</li><li>
Demonstrated track record of deploying machine learning models into production.</li></ul>
Technical Skills<p>
Strong expertise in:
</p><ul><li><ul><li>Machine Learning</li><li>
Statistical Modeling</li><li>
Predictive Analytics</li><li>
Deep Learning</li><li>
NLP and/or Generative AI</li><li>
Experiment Design and A/B Testing</li></ul></li></ul><p>
Advanced proficiency in:
</p><ul><li><ul><li>Python</li><li>
SQL</li><li>
Data Visualization tools</li></ul></li></ul><p>
Experience with:
</p><ul><li><ul><li>MLOps practices</li><li>
Model monitoring and governance</li><li>
Cloud platforms (Azure, AWS, or GCP)</li><li>
Data Engineering concepts and modern data platforms</li></ul></li></ul><p>
Familiarity with:
</p><ul><li><ul><li>LLMs and Generative AI applications</li><li>
Feature stores</li><li>
Recommendation systems</li><li>
Real-time machine learning solutions</li></ul></li></ul>
Preferred Qualifications<ul><li>
Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, or a related field.</li><li>
Experience within FinTech, Digital Products, E-commerce, Banking, or Technology organizations.</li><li>
Experience managing large-scale data platforms and AI initiatives.</li><li>
Knowledge of modern software engineering practices and DevOps methodologies.</li></ul><br>
<b>
Benefits</b><br>
<ul><li>
Lead cutting-edge AI and Data Science initiatives.</li><li>
Build products impacting millions of users.</li><li>
Work with highly talented engineering and product teams.</li></ul><ul><li>
Shape the future of data-driven decision making within the organization.
</li><li>When you come to our b_labs office, you'll find creative workspaces and an open design to foster collaboration between teams.
</li><li>You know best whether you want to work from home or in the office.
</li><li>From &quot;Day 1&quot; you will receive all the equipment you need be successful at work.</li></ul></div>

Engineering Manager (Data Science)

Egen Solutions Inc

<div><div><div><div><b>Job Description :</b></div>
<div></div>
<div>We are seeking a highly motivated and experienced Lead ML Engineer to join our growing ML/GenAI team.</div>
<div></div>
<div>You will play a key role in designing, developing and productionalizing ML/GenAI applications by evaluating models, training and/or fine tuning them. As a lead, you require a deep understanding of both machine learning algorithms and software architecture. You need to take ownership of projects from conception to deployment, collaborating with engineers and stakeholders to ensure successful project delivery.</div>
</div></div><div><div><h3 class="jobSectionHeader"><b>What we're looking for:</b></h3><div><div><div>
<ul><li>At least 5 years of experience in designing &amp; building ML/AI applications for customer and deploying them into production</li>
<li>At least 8 years of Software engineering experience in building Secure, scalable and performant applications for customers.</li>
<li>At least 2 years of experience leading and mentoring ML/data science teams( 4+ team members)</li>
<li>Experience with Document extraction using AI, Conversational AI, Vision AI, NLP or Gen AI.</li>
<li>Design, develop, and operationalize existing ML models by fine tuning, personalizing it.</li>
<li>Evaluate machine learning models and perform necessary tuning.</li>
<li>Develop prompts that instruct LLM to generate relevant and accurate responses.</li>
<li>Collaborate with data scientists and engineers to analyze and preprocess datasets for prompt development, including data cleaning, transformation, and augmentation.</li>
<li>Conduct thorough analysis to evaluate LLM responses, iteratively modify prompts to improve LLM performance.</li>
<li>Lead the end-to-end design and architecture of scalable, reliable, and cost-effective Generative AI solutions. This includes designing RAG (Retrieval-Augmented Generation) pipelines, agentic workflows, and model fine-tuning strategies.</li>
<li>Hands on customer experience with RAG solution or fine tuning of LLM model.</li>
<li>Build and deploy scalable machine learning pipelines on Google Cloud or any equivalent cloud platform involving data warehouses, machine learning platforms, dashboards or CRM tools.</li>
<li>Experience working with the end-to-end steps involving but not limited to data cleaning, exploratory data analysis, dealing outliers, handling imbalances, analyzing data distributions (univariate, bivariate, multivariate), transforming numerical and categorical data into features, feature selection, model selection, model training and deployment.</li>
<li>Act as the senior-most developer, writing clean, high-quality, and scalable code. This includes building core components for prompt engineering, vector search, data processing, model evaluation, and inference serving.</li>
<li>Proven experience building and deploying machine learning models in production environments for real life applications</li>
<li>Good understanding of natural language processing, computer vision or other deep learning techniques.</li>
<li>Expertise in Python, Numpy, Pandas and various ML libraries (e.g., XGboost, TensorFlow, PyTorch, Scikit-learn, LangChain).</li>
<li>Familiarity with Google Cloud or any other Cloud Platform</li>
</ul></div></div></div></div></div><div><div><h3 class="jobSectionHeader"><b>Good to Have
</b></h3><div><div><div><ul><li>Google Cloud Certified Professional Machine Learning or TensorFlow Certified Developer certifications or equivalent.</li>
<li>Experience of working with one or more public cloud platforms - namely Google Cloud, AWS or Azure.</li>
<li>Experience with AutoML and vision techniques.</li>
<li>Master&rsquo;s degree in statistics, machine learning or related fields.</li>
</ul></div></div></div></div></div><div><div>We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.</div></div></div>

Lead-ML Engineer

BlackLine

<div>Make Your Mark::
<div>
We&rsquo;re looking for a Senior AI/ML Engineer to design, build, and optimize data pipelines that power our next-generation AI-driven accounting agents. You&rsquo;ll lead the development of scalable, high-performance data infrastructure while collaborating closely across teams.</div><div><br>
Responsibilities:</div><ul><li><b>
Lead data pipeline development:</b> Build and maintain PySpark ETL pipelines with high data quality and performance</li><li><b>
Manage integrations:</b> Establish robust connections to client data sources via APIs and tools like FiveTran, Plaid, and BlackLine&rsquo;s own internal connector ecosystem</li><li><b>
Ensure reliability:</b> Monitor pipeline performance, automate testing, and validate data accuracy</li><li><b>
Optimize for scale:</b> Implement performance improvements (e.g., CDC mechanisms, indexing strategies) for large-scale datasets</li><li><b>
Collaborate &amp; innovate:</b> Work with business stakeholders to refine data requirements and integrate cutting-edge AI and big data technologies</li></ul>
You'll Get To::
<div><b>
Leadership and Strategy</b></div><ul><li>
Partner with data science, security, and product teams to set evaluation and governance standards (Guardrails, Bias, Drift, Latency SLAs).</li><li>
Mentor senior engineers and drive design reviews for ML pipelines, model registries, and agentic runtime environments.</li><li>
Lead incident response and reliability strategies for ML/AI systems.</li></ul><div><b>
AI System Deployment and Integration:</b></div><ul><li>
Collaborate with development teams to integrate AI solutions into existing workflows and applications.</li><li>
Ensure seamless integration with different platforms and technologies.</li><li>
Define and manage MCP Registry for agentic component onboarding, lifecycle versioning, and dependency governance.</li><li>
Build CI/CD pipelines automating LLM agent deployment, policy validation, and prompt evaluation of workflows.</li><li>
Develop and operationalize experimentation frameworks for agent evaluations, scenario regression, and performance analytics.</li><li>
Implement logging, metering, and auditing for agent behavior, function calls, and compliance alignment.</li><li>
Create scalable observability systems&mdash;tracking conversation outcomes, factual accuracy, latency, escalation patterns, and safety events.</li><li>
Architect end-to-end guardrails for AI agents including prompt injection protection, identity-aware routing, and tool usage authorization.</li><li>
Collaborate cross-functionally to standardize authentication, authorization, and session governance for multi-agent runtimes.</li></ul><div><b>
Model Deployment and Integration</b>:</div><ul><li>
Architect and standardize model registries and feature stores to support version tracking, lineage, and reproducibility across environments.</li><li>
Lead the deployment of machine learning models into production environments, ensuring scalability, reliability, and efficiency.</li><li>
Collaborate with software engineers to integrate machine learning models into existing applications and systems.</li><li>
Implement and maintain APIs for model inference.</li></ul><div><b>
Infrastructure and Environment Management</b>:</div><ul><li>
Design and manage training infrastructure including distributed training orchestration, GPU/TPU resource allocation, and automatic scaling.</li><li>
Implement CI/CD for model workflows using pipelines integrated with model validation, bias checks, and rollback automation.</li><li>
Build standardized experimentation frameworks for reproducible training, tuning, and deployment cycles (MLflow, W&amp;B, Kubeflow).</li><li>
Manage and optimize the infrastructure required for machine learning operations in cloud.</li><li>
Work closely with other teams to ensure the availability, security, and performance of machine learning systems.</li></ul><div><b>
Monitoring and Maintenance:</b></div><ul><li>
Implement robust monitoring solutions for deployed machine learning models to detect issues and ensure performance.</li><li>
Collaborate with data scientists and engineers to address and resolve model performance and data quality issues.</li><li>
Conduct regular system maintenance, updates, and optimizations to ensure optimal performance of machine learning solutions.</li></ul><div><b>
Automation and Orchestration:</b></div><ul><li>
Develop and maintain automation scripts and tools for managing machine learning workflows.</li><li>
Implement orchestration systems to streamline the end-to-end machine learning lifecycle, from data preparation to model deployment.</li></ul><div><b>
Collaboration with Data Science Teams:</b></div><ul><li>
Collaborate with data scientists to understand model requirements and constraints for deployment.</li><li>
Facilitate the transition of machine learning models from research to production, ensuring scalability and efficiency.</li></ul><div><b>
Performance Optimization:</b></div><ul><li>
Identify and implement optimizations to enhance the performance and efficiency of machine learning models in production.</li><li>
Conduct performance analysis and implement improvements based on resource utilization of metrics.</li></ul><div><b>
Security and Compliance:</b></div><ul><li>
Implement security measures to protect machine learning systems and data.</li><li>
Ensure compliance with regulatory requirements and industry standards related to machine learning and data privacy.</li><li>
Integrate audit controls, metadata storage, and lineage tracking across ML and AI workflows.</li><li>
Ensure complete monitoring and feedback loops including event logs, evaluations, and automated retraining triggers.</li><li>
Enforce secure deployment patterns with Infrastructure-as-Code and cloud-native secrets management.</li><li>
Define SLAs, error budgets, and compliance reporting mechanisms for ML and AI systems.</li></ul>
What You'll Bring::
<ul><li>3+ years of experience with programming skills in languages such as Python, Java, or Scala.</li><li>
Expertise in ML frameworks (TensorFlow, PyTorch, scikit-learn) and orchestration tools (Airflow, Kubeflow, Vertex AI, MLflow).</li><li>
Proven experience operating production pipelines for ML and LLM-based systems across cloud ecosystems (GCP, AWS, Azure).</li><li>
Deep familiarity with LangChain, LangGraph, ADK or similar agentic system runtime management.</li><li>
Strong competencies in CI/CD, IaC, and DevSecOps pipelines integrating testing, compliance, and deployment automation.</li><li>
Hands-on with observability stacks (Prometheus, Grafana, Newrelic) for model and agent performance tracking.</li><li>
Understanding of governance frameworks for Responsible AI, auditability, and cost metering across training and inference workloads.</li><li>
Proficiency in containerization technologies (e.g., Docker, Kubernetes).</li></ul>
We&rsquo;re Even More Excited If You Have::
<div><b>
Operations and Infrastructure:</b></div><ul><li>
Proficient in scripting languages (e.g., Bash, python) for automation.</li><li>
Experience with workflow orchestration tools (e.g., Apache Airflow).</li><li>
Expertise in managing and optimizing cloud-based infrastructure.</li><li>
Familiarity with DevOps practices and tools for automated deployment.</li><li>
Understanding of network configurations and security protocols.</li></ul><div><b>
Problem-solving and Critical Thinking</b>:</div><ul><li>
Ability to define problems, collect and analyze data, and propose innovative solutions. Strong critical thinking skills to evaluate models, identify limitations, and</li></ul><div><b>
Adaptability and Learning Agility</b>:</div><ul><li>
Comfortable working in a fast-paced, rapidly evolving environment. Proactive in staying up to date with the latest trends, techniques, and technologies in AI/data science</li></ul>
Thrive at BlackLine Because You Are Joining::
<ul><li>A technology-based company with a sense of adventure and a vision for the future. Every door at BlackLine is open. Just bring your brains, your problem-solving skills, and be part of a winning team at the world's most trusted name in Finance Automation!</li><li>
A culture that is kind, open, and accepting. It's a place where people can embrace what makes them unique, and the mix of cultural backgrounds and varying interests cultivates diverse thought and perspectives.</li><li>
A culture where BlackLiner's continued growth and learning is empowered. BlackLine offers a wide variety of professional development seminars and inclusive affinity groups to celebrate and support our diversity.</li></ul><div>
BlackLine is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity or expression, race, ethnicity, age, religious creed, national origin, physical or mental disability, ancestry, color, marital status, sexual orientation, military or veteran status, status as a victim of domestic violence, sexual assault or stalking, medical condition, genetic information, or any other protected class or category recognized by applicable equal employment opportunity or other similar laws</div><div>
BlackLine recognizes that the ways we work and the workplace itself has shifted. We innovate in a workplace that optimizes a combination of virtual and in-person interactions to maximize collaboration and nurture our culture. Candidates who live within a reasonable commute to one of our offices will work in the office at least 3 days a week.</div>
Salary Range:: USD $145,000.00/Yr. - USD $182,000.00/Yr.</div>

Senior Software Engineer AI

Alignerr

<div>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 What if your machine learning expertise could directly influence how the most advanced AI systems in the world think, reason, and write code? We're looking for experienced ML engineers in Berlin to evaluate AI-generated machine learning solutions &mdash; catching errors, improving quality, and helping frontier AI models get genuinely better at one of the hardest things they do.
 <br/>
 <br/>
 This is a fully remote, flexible contract role. Work asynchronously on your own schedule. No fixed hours, no meetings &mdash; just high-impact, expert work that matters.
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 <br/>
 <ul>
  <li>
   Organization: Alignerr
  </li>
  <li>
   Type: Hourly Contract
  </li>
  <li>
   Location: Remote (Germany-based)
  </li>
  <li>
   Commitment: Flexible, project-based
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What You'll Do
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Review and evaluate AI-generated machine learning code &mdash; including Python, TensorFlow, PyTorch, and scikit-learn &mdash; for correctness, efficiency, scalability, and clarity
  </li>
  <li>
   Write high-quality ML solutions to modeling, data processing, and deployment problems across a range of difficulty levels
  </li>
  <li>
   Craft clear, developer-friendly explanations for model architecture decisions, code logic, and problem-solving approaches
  </li>
  <li>
   Identify edge cases, ambiguities, and weaknesses in problem statements, datasets, or AI-generated responses
  </li>
  <li>
   Help set the quality bar for how AI understands and produces machine learning code
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Who You Are
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Deeply fluent in machine learning &mdash; you know your way around model development, data preprocessing, training pipelines, and deployment
  </li>
  <li>
   Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn
  </li>
  <li>
   Strong written communicator &mdash; able to explain complex ML concepts clearly and precisely in English
  </li>
  <li>
   Detail-oriented and rigorous &mdash; you catch what others miss and care about getting things right
  </li>
  <li>
   Self-motivated and comfortable working independently in an async environment
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Nice to Have
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   3&ndash;5+ years working on machine learning projects, pipelines, or MLOps
  </li>
  <li>
   Experience with model evaluation, cloud deployment, or production ML systems
  </li>
  <li>
   Bachelor's, Master's, or PhD in Computer Science, Machine Learning, or a related field
  </li>
  <li>
   Background in data labeling, RLHF, or other AI training workflows
  </li>
  <li>
   Prior experience with code review or technical writing
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Why Join Us
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Work on cutting-edge AI projects alongside leading research labs and top AI teams
  </li>
  <li>
   Fully remote and async &mdash; work when and where it suits you, with no minimum hour commitments beyond project needs
  </li>
  <li>
   Freelance autonomy with the structure of meaningful, task-based work
  </li>
  <li>
   Your contributions directly improve AI models used by top research labs and enterprise teams worldwide
  </li>
  <li>
   High-performing contributors take on expanded responsibilities and lead new programs
  </li>
  <li>
   Potential for ongoing work and contract extension as new projects launch
  </li>
 </ul>
</div>


Software Engineer – Machine Learning (AI Training)

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