machine learning intern

Delta Air Lines

<div><div><div><div><div><p><b>United States, Georgia, Atlanta</b></p>
<p><b>Information Technology</b></p>
<p><b>15-Jun-2026</b></p>
<p><b>Ref #: 32774</b></p>
</div></div></div></div><div><div><div><div><h3 class="jobSectionHeader"><b>How you'll help us Keep Climbing (overview &amp; key responsibilities)</b></h3>
</div></div><div><div><p>At Delta Air Lines, we are continually looking to build a high performing, self-motivated team of technologists who embrace new technologies to enhance the customer and employee experience.</p>
<p>We are looking for an <b>Innovation &amp; AI Engineering Intern</b> to design and develop machine learning and AI-based products that incorporate cutting-edge technology. Just a heads up, this isn&rsquo;t a typical engineering role.</p>
<p>As an<b> Innovation &amp; AI Engineering Intern </b>at Delta, you will own projects from day 1. You will be responsible for:</p>
<ul><li>Engaging with business stakeholders and customers to identify problem areas</li>
<li>Developing and modifying state-of-the-art ML models to build robust and holistic solutions</li>
<li>Collaborating with other engineers, strategists, and designers to think of customer experiences that can be transformed by machine learning and AI</li>
<li>Presenting project updates to leaders across multiple business units</li>
<li>Leveraging advancements in technology and brainstorming ways to incorporate them into different areas of Delta</li>
</ul></div></div></div></div><div><div><div><div><h3 class="jobSectionHeader"><b>Benefits and Perks to Help You Keep Climbing</b></h3>
</div></div><div><div><ul><li>Experience travel and culture through Delta&rsquo;s unmatched flight benefits</li>
<li>Incredibly passionate, empathetic, and truly talented team members across engineering, strategy, venture, and design functions</li>
<li>Freedom of working on a small team while having the impact of a team that drives innovation forward at a huge company</li>
<li>Excitement of working on customer-facing projects that can ship within weeks</li>
<li>Offices located in Midtown in Atlanta, adjacent to Georgia Tech campus, and near Delta HQs</li>
</ul></div></div></div></div><div><div><div><div><h3 class="jobSectionHeader"><b>What you need to succeed (minimum qualifications)</b></h3>
</div></div><div><div><div><ul><li>Experience developing machine learning models (e.g., neural networks, deep reinforcement learning, gradient boosted trees, etc.) using Python, TensorFlow, PyTorch, or other machine learning platforms</li>
<li>Must be actively enrolled in an undergraduate accredited college, university, or institution during the duration of the program.</li>
<li>Understanding of machine learning best practices such as training/serving models, feature engineering, and feature/model selection</li>
<li>Knowledgeable about different machine learning domains like natural language processing, computer vision, personalization and recommendation, and anomaly detection</li>
<li>Flexibility to learn and work on things outside of your comfort zone</li>
<li>You&rsquo;re self-driven, take pride in your work, and find satisfaction in building interesting things</li>
<li>You can adapt and explain a neural network to your lead engineer and to a 5-year-old</li>
<li>You embrace different perspectives and styles of thinking</li>
<li>Demonstrates that privacy is a priority when handling personal data</li>
<li>Embraces a diverse set of people, thinking and styles</li>
<li>Consistently makes safety and security, of self and others, the priority</li><br>
</ul><br>
</div><ul><li><i>Consistently prioritizes safety and security of self, others, and personal data.</i>
</li><li><i>Embraces diverse people, thinking, and styles.</i>
</li><li><i>Possesses a high school diploma, GED, or high school equivalency.</i>
</li><li><i>Is at least 18 years of age and has authorization to work in the United States.</i>
</li></ul></div></div></div></div><div><div><div><div><h3 class="jobSectionHeader"><b>What will give you a competitive edge (preferred qualifications)</b></h3>
</div></div><div><ul><li></li></ul></div></div></div></div><div></div>

Intern, Innovation - AI Engineering (Fall 2026)

Better Analytics Private Limited

<p>We are looking for a motivated AI/ML Intern to join our team and work on real-world machine learning and generative AI projects. This internship offers hands-on experience in building, training, and deploying AI models while collaborating with experienced engineers and product teams.</p><p><b>Key Responsibilities</b></p><ul><li>Assist in developing and implementing machine learning models.</li><li>Work with structured and unstructured datasets for data preprocessing and analysis.</li><li>Build and evaluate predictive models using Python and popular ML libraries.</li><li>Develop AI-powered applications using Large Language Models (LLMs) and prompt engineering.</li><li>Experiment with Retrieval-Augmented Generation (RAG) and vector databases.</li><li>Support model deployment, testing, and performance optimization.</li><li>Research emerging AI technologies and contribute innovative ideas.</li><li>Document experiments, findings, and technical implementations.</li></ul><p><b>Required Skills</b></p><ul><li>Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.</li><li>Strong programming skills in Python.</li><li>Basic understanding of machine learning concepts and algorithms.</li><li>Familiarity with libraries such as Scikit-learn, Pandas, NumPy, TensorFlow, or PyTorch.</li><li>Knowledge of SQL and data analysis.</li><li>Understanding of Generative AI, LLMs, or prompt engineering is a plus.</li><li>Strong analytical and problem-solving skills.</li><li>Good communication and teamwork abilities.</li></ul><p><b>Preferred Qualifications</b></p><ul><li>Experience with LangChain, LlamaIndex, or similar AI frameworks.</li><li>Familiarity with APIs, REST services, or FastAPI.</li><li>Knowledge of Git and version control.</li><li>Experience with cloud platforms (AWS, Azure, or GCP) is a plus.</li><li>Personal, academic, or open-source AI/ML projects are highly valued.</li></ul><p><b>Internship Details</b></p><ul><li><b>Employment Type:</b> Internship</li><li><b>Duration:</b> 3&ndash;6 months</li><li><b>Work Mode:</b> On-site</li></ul><p>Pay: ₹15,000.00 - ₹20,000.00 per month</p><p>Work Location: In person</p>

AI/ML Intern (Machine Learning & Generative AI)

kaiko.ai

<div>
 <strong>
  About Kaiko
  <br/>
  <br/>
 </strong>
 kaiko.ai is a clinical AI research lab in Zurich and Amsterdam. We train our own large-scale frontier-class models end to end, on our own compute. The full stack is in scope, from training infrastructure and post-training algorithms to data generation, evaluation, and production inference.
 <br/>
 <br/>
 Our models are developed and deployed at leading European hospitals, and that deployment feeds back into the next training cycle.
 <br/>
 <br/>
 We're hiring interns across the lab. You'll work on the real problems of training and serving these models in a regulated clinical setting.
 <br/>
 <br/>
 <strong>
  The Opportunity
  <br/>
  <br/>
 </strong>
 As an ML Research Intern, you will be embedded in our core research team for six months, working alongside PhD researchers and senior engineers on problems that directly shape our clinical foundation model. You will own real work, contribute ideas, and see your output reflected in our system.
 <br/>
 <br/>
 Depending on your background and preferences, your project may sit in one of the following areas:
 <br/>
 <br/>
 <ul>
  <li>
   Data: Synthetic clinical data generation, multimodal data pipelines, curation and quality filtering.
  </li>
  <li>
   Evaluation: Clinical benchmarks, agentic eval design, measurement infrastructure for the production stack.
  </li>
  <li>
   Scaling: Continued pre-training on clinical corpora, post-training algorithms, distributed training at frontier scale.
  </li>
  <li>
   RL: Agentic RL on real clinical workflows, reward modeling, RL infrastructure.
  </li>
  <li>
   Acceleration: Inference &amp; Training optimisation, serving stack, quantisation and throughput tuning.
   <br/>
   <br/>
  </li>
 </ul>
 You will discuss and agree on your specific focus during the interview process, based on mutual fit and current priorities.
 <br/>
 <br/>
 <strong>
  Who You Are
  <br/>
  <br/>
 </strong>
 We are looking for MSc students or recent graduates in machine learning, computer science, or a related quantitative field. We care more about sharp thinking, high agency, and genuine curiosity than a perfect CV.
 <br/>
 <br/>
 <strong>
  You should bring:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Strong programming in Python and comfort with ML frameworks (PyTorch or equivalent).
  </li>
  <li>
   Hands-on experience with ML research or engineering, ideally in training, post-training, RL, data, or evaluation. Coursework, thesis, internship, or open-source all count.
  </li>
  <li>
   Clear technical communication, in design docs and in discussion with researchers, engineers, and clinical scientists.
  </li>
  <li>
   Motivation to work on hard problems with real ownership. Intern projects ship into the live training and serving stack.
   <br/>
   <br/>
  </li>
 </ul>
 The specific area depends on the project. None of these are required upfront.
 <br/>
 <br/>
 <strong>
  Why kaiko
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Work at the frontier: you will be in the room with PhD researchers and engineers who have built production ML systems at top labs and institutions. Expect to be challenged and to grow fast.
  </li>
  <li>
   Ownership: you will set goals, make decisions, and present your findings directly to the research team, not to an intern coordinator.
  </li>
  <li>
   Conversion pathway: strong interns are actively considered for full-time roles. This is how we build the team.
  </li>
  <li>
   Fair compensation: an internship salary of CHF4000/EUR3000 gross per month
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Interview Process
  <br/>
  <br/>
 </strong>
 We keep it fast. The process typically involves three steps:
 <br/>
 <br/>
 <ul>
  <li>
   Screening call (30 min): motivation, background, and initial fit.
  </li>
  <li>
   Technical assessment: a short, focused problem relevant to your area, reviewed together in a follow-up conversation.
  </li>
  <li>
   Onsite or video interview: meet the team, go deeper on your thinking, and align on project fit.
   <br/>
   <br/>
  </li>
 </ul>
 We review applications on a rolling basis. If you are finishing your degree this summer and want to start in September, apply now.
</div>


ML Research Graduate Internship

RoboService

<div>
 <p>
  <strong>
   Company Description
  </strong>
 </p>
 <p>
  RoboService solves the "Last Mile" of humanoid robotics. While manufacturers provide the hardware and foundation models, these general-purpose "brains" are not yet ready for the specific, accurate tasks of a production line. We bridge that gap.
 </p>
 <p>
  <br/>
 </p>
 <p>
  We don't build foundation models from scratch; we operationalize them. We take state-of-the-art VLA models and fine-tune them for reliability, speed, and precision in real-world manufacturing environments.
 </p>
 <p>
  <br/>
 </p>
 <p>
  We are not a research lab; we are shipping code that moves atoms. Launched in July 2025 by repeat founders with successful exits, we are looking for engineers who want to take robots out of the lab and onto the factory floor.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Role Description
  </strong>
 </p>
 <p>
  We are looking for an intern / working student who joins our Robotics Machine Learning Engineering team. You will bridge the gap between "remote controlled hardware" and "autonomous robots". We work with robotics manufacturers that provide great hardware and a model infrastructure, but are missing the software to fine-tune the models on a specific task. Your primary focus will be establishing training pipelines - from teleoperation data collection to fine-tuning VLA models and utilizing Reinforcement Learning (RL) to fine-tune complex manipulation tasks.
 </p>
 <p>
  <br/>
 </p>
 <p>
  You won't be writing papers. You will be:
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   Building
   <strong>
    data pipelines
   </strong>
   to capture and analyze training data
  </li>
  <li>
   Fine-tuning
   <strong>
    VLA models
   </strong>
   (open source and proprietary models from our partners)
  </li>
  <li>
   Managing the
   <strong>
    Data Pipeline
   </strong>
   and overseeing the
   <strong>
    Teleoperation
   </strong>
   activities. Manage large datasets required for fine-tuning models.
  </li>
  <li>
   <strong>
    Reinforcement Learning
   </strong>
   (RL): Apply RL techniques to fine-tune robot actions, ensuring robust performance when the robot works on the production line.
  </li>
  <li>
   Utilize high-fidelity simulation environments (
   <strong>
    MuJoCo
   </strong>
   ,
   <strong>
    NVIDIA Isaac Sim, Omniverse
   </strong>
   ) to train and test agents before deploying them to physical hardware. (Sim2Real)
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Qualifications
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Education
   </strong>
   : Currently pursuing your Master&rsquo;s degree or PhD in Robotics, Computer Science, Data Science, Artificial Intelligence, or a related field.
  </li>
  <li>
   <strong>
    Experience
   </strong>
   : Machine Learning, Deep learning, or embodied AI. Hands-On Robotics Experience.
  </li>
  <li>
   <strong>
    Core ML Skills
   </strong>
   : Strong proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, or JAX). Experience with Transformers and VLA architectures is highly desirable.
  </li>
  <li>
   <strong>
    Simulation
   </strong>
   : Proven experience with physics-based simulators, specifically NVIDIA Isaac Sim or similar (Gazebo, MuJoCo).
  </li>
  <li>
   <strong>
    Data Engineering:
   </strong>
   Ability to analyze and manage large datasets, automate data cleaning, and build training pipelines.
  </li>
  <li>
   Proficiency in
   <strong>
    English
   </strong>
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What We Offer
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   <strong>
    Path to Full-Time
   </strong>
   : After a successful internship, we aim to extend a full-time offer.
  </li>
  <li>
   <strong>
    Berlin based
   </strong>
   : We&rsquo;re an in-person team and we work out of our office in downtown Berlin. If you're not in Berlin yet, be prepared to move here before the start of the job.
  </li>
  <li>
   <strong>
    Access to Cutting Edge Tech
   </strong>
   : Work daily on the latest software and hardware that will shape our future.
  </li>
  <li>
   <strong>
    Impact
   </strong>
   : Work in real projects with manufacturers to bring robots onto manufacturing floors.
  </li>
  <li>
   <strong>
    Startup Environment
   </strong>
   : We are a fast-moving startup with high growth ambitions.
  </li>
  <li>
   <strong>
    Team of Experts
   </strong>
   : We are a team of experts where every voice matters. Work with professionals that are leading their field.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Apply now!
  </strong>
 </p>
</div>


Internship - Data Science & Robotics Machine Learning

NXP Semiconductors

<div><div><div><p><b>The future starts here! Ready to join NXP </b><b>?
</b></p></div><div><p>Become part of a dynamic Product Engineering team that is working on products driving One of the mega trends in the evolution towards highly automated vehicles. NXP offers sensor and processing technology that drives all aspects of the secure connected cars of today and the autonomous cars of tomorrow. Product line In-Vehicle Networking is with CAN, LIN, Flexray and Ethernet solutions, enabling communications within architectures designed for secure and hyper-connected autonomous vehicles.<br>
</p></div><p></p><div><p><b>Your Team
</b></p></div><div><p>The Product Engineering:
</p></div><div><p>You will be part of our product development team , Product Line, In-Vehicle Networking, in Nijmegen, Netherlands, who is working rigorously to deliver the best products to market on time while ensuring our brand's reputation for leadership in total quality at optimal cost.
</p></div><div><p>As a Product Engineer ing intern , you are in a central position (a spider in the web) in the New IC Product development . You get to work with all the disciplines needed to design an IC and several external teams to prepare it for mass production . There is a lot of room for new ideas and innovations and you will be supported to have a continuous focus on development, coaching and creating a supportive environment from your team.<br>
</p></div><p></p><div><p><b>Your Responsibilities
</b></p></div><div><ul><li><p>Using your knowledge of artificial intelligence and machine learning develop innovative solutions to use within Product Engineering at NXP .
</p></li></ul></div><div><ul><li><p>You analyze semiconductor test &amp; characterization data using Statistical Data Analysis Tools.
</p></li></ul></div><div><ul><li><p>You will be part of internal project sub-teams and supporting external interfaces. You work closely with the team lead to execute changes across functions to deliver your result on time, at optimal quality and cost.
</p></li></ul></div><div><ul><li><p>Support development of New Machine learning solutions to provide best in class Data analytic s to the Product Engineering team.
</p></li></ul></div><div><ul><li><p>You support the vision of product quality by implementing the best zero-defect screening methods and by continuously searching for the best screening techniques that meet the increasing market demand.<br>
</p></li></ul></div><p></p><div><p><b>What&rsquo;s </b><b>in it for you
</b></p></div></div><div><div><ul><li><p>A great opportunity to develop your skills (technical, soft skills, communication, etc.)
</p></li></ul></div><div><ul><li><p>Gaining experience in a multinational and diverse environment
</p></li></ul></div><div><ul><li><p>Possibility to become part of NXP&rsquo;s Young Professional Talent Pool
</p></li></ul></div><div><ul><li><p>Working on real assignments which contribute to NXP&rsquo;s objectives<br>
</p></li></ul></div><p></p><div><p><b>Your </b><b>P </b><b>rofile
</b></p></div><div><ul><li><p>Master&rsquo;s student with major in Computer Science, Machine Learning, Data Science, or a closely related quantitative field . Additional course work in Electronics and/or VLSI Design is a plus.
</p></li></ul></div><div><ul><li><p>Strong programming skills in Python and experience working with data analysis or machine learning workflows.
</p></li></ul></div><div><ul><li><p>Comfortable translating analytical results into practical engineering decisions and collaborating with cross-functional technical stakeholders.
</p></li></ul></div><div><ul><li><p>Interest in semiconductor test data, production analytics, and developing ML solutions in an industrial setting.
</p></li></ul></div><div><ul><li><p>Available for a minimum 6 months of internship.<br>
</p></li></ul></div><p></p><div><p><b>Duration
</b></p></div><div><p>This is a full-time internship ( 40 hours per week) with a duration of 6 months or longer.
</p></div><div><p>Please note that in order to be considered for an internship/working student assignment, you need to be registered as a student during the entire period.
</p></div><p></p><div><p><b>Creating Secure Connections and Infrastructure for a Smarter World
</b></p></div><div><p>NXP Semiconductors N.V. (NASDAQ: NXPI) makes products and environments safer, more sustainable, and more secure with innovative connectivity and edge processing solutions for a smarter world.
</p></div><div><p>We are in the business of better . Not just better technologies, but better innovations to improve society. As the world leader in secure connectivity and processing solutions for embedded applications, NXP is solving the world&rsquo;s most complex technology challenges to accelerate business innovation, enhance how we work, and advance how we live.
</p></div><div><p>If you are as excited about this opportunity as we are, we kindly invite you to apply. After a screening based on your profile you can be expected to have a video interview with our Talent Acquisition Consultant followed by business.
</p></div><p></p><div><p><b>What </b><b>C </b><b>an </b><b>Y </b><b>ou </b><b>E </b><b>xpect?
</b></p></div></div><div><p>Development opportunities: We believe that a key component to growing our business is to develop our people. To enable you to grow your career at NXP, we provide you with a mix of learning through on-the-job experiences, learning from industries bests, and learning through education to help you develop your core and professional skills.
</p></div><div><p>Our offices: The Netherlands is home to our global headquarters (Eindhoven) along with two additional sites (Nijmegen, Delft) and includes a diverse team of over 2000 employees with 51 different nationalities focused on R&amp;D, manufacturing, product development, business operations, legal and sales.
</p></div><div><p>Hiring process: Applying only takes a minute! Fill in the online application and share your CV with us. After a positive screening based on your CV you will have an initial video conversation with our Talent Acquisition Consultant followed by several business interviews. Here are some useful tips to help you prepare .
</p></div><div><p>And more: Life at NXP is more than work alone. Join one of the many social activities that are organized by and for employees in the Netherlands, such as our Christmas parties and International Walking Day. We have a YOUNG community that organizes a mix of social and professional events for our young professionals and an active Women in NXP. We also take time to give back to our communities by engaging young girls to learn about Technology during Girls Day or participating in several volunteering activities.<br>
<br>
</p></div><div><p><b>What&rsquo;s </b><b>N </b><b>ext?
</b></p></div><div><p>If you&rsquo;re excited about this opportunity, we kindly invite you to apply! If you have any questions, we are happy to answer them.
</p></div><p></p><p>More information about NXP in the Netherlands...
</p><p></p>#LI-9c8e</div>

Internship – Product Engineering (ML Model Development)

Desmata Inc

<p><b>Job Title: Machine Learning Engineer - Hybrid NYC</b><br/><b>Location: New York, NY</b></p><p><b>Role Overview:</b></p><p><b>Technical Skills</b></p><p><b>Must Have</b></p><p>Applied Machine Learning<br/>Azure Databricks<br/>Big Data Analytics<br/>Databricks Certified Data Engineer Associate<br/>Data Structures<br/>Google Cloud Certified Machine Learning Engineer<br/>Machine Learning Operations<br/>Pandas Python Library<br/>PySpark</p><p><b>Job Description</b></p><ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or related field.</li><li>Strong experience in machine learning algorithms, predictive modeling, and data mining.</li><li>Proficiency in PySpark, Python Pandas (required) for data science workloads.</li><li>Strong SQL (required) knowledge and experience with relational databases.</li><li>Minimum 3 years of experience with data visualization tools such as Power BI, DAX Queries, and best practices.</li><li>Experience with Azure Databricks, Google Cloud, and modern data science libraries (e.g., scikit-learn, pandas, NumPy).</li><li>Experience with GenAI and large language models.</li><li>Ability to interpret complex datasets and produce actionable insights.</li><li>Must know how to analyze the root cause of dashboard errors.</li><li>Have experience in ML Ops and have a strong coding background.</li><li>Have experience with Natural Language Processing (NLP).</li><li>Knowledge or experience with A/B Testing.</li><li>Working knowledge of designing, training, and implementing machine learning models.</li><li>Familiarity with cloud-based infrastructure.</li><li>Excellent communication and problem-solving skills.</li><li>7 or more years of experience in data science and machine learning engineering.</li><li>Additional Skills (Skills that are a plus, but not required)</li><li>Knowledge of statistical methods and experimental design.</li></ul><p><b>Responsibilities</b></p><p><b>Advanced Analytics &amp; Machine Learning</b></p><ul><li>Design, develop, and optimize machine learning models (forecasting, classification, clustering).</li><li>Apply data mining techniques to uncover patterns and insights in large datasets.</li><li>Perform feature engineering, model validation, and performance tuning.</li><li>Explore and deploy modern AI and ML approaches to enhance automation and analytics.</li></ul><p><b>Data Preparation &amp; Quality</b></p><ul><li>Prepare structured and unstructured data for modeling and advanced analysis.</li><li>Develop scripts and tools for data cleansing, validation, and enrichment.</li><li>Collaborate with Data Engineering to maintain efficient data pipelines.</li><li>Identify data quality issues and propose remediation.</li></ul><p><b>Analytics, Insights &amp; Reporting</b></p><ul><li>Conduct deep-dive analyses to identify trends and improvement opportunities.</li><li>Communicate complex findings in clear, concise ways to technical and non-technical stakeholders.</li><li>Support the development of dashboards, metrics, and analytical solutions.</li></ul><p><b>Cross-Team Collaboration</b></p><ul><li>Work with architects, engineers, and analysts to define analytical requirements.</li><li>Contribute to conceptual data model design and workflow optimization.</li><li>Promote best practices in machine learning, analytics, and data governance.</li></ul><p>Pay: From $55.00 per hour</p><p>Work Location: In person</p>

Machine Learning Engineer

CapTech

<div>
 <p>
  CapTech is an award-winning consulting firm that collaborates with clients to achieve what&rsquo;s possible through the power of technology. At CapTech, we&rsquo;re passionate about the work we do and the results we achieve for our clients. From the outset, our founders shared a collective passion to create a consultancy centered on strong relationships that would stand the test of time. Today we work alongside clients that include Fortune 100 companies, mid-sized enterprises, and government agencies, a list that spans across the country.
  <br/>
  <br/>
 </p>
 <p>
  <br/>
  <br/>
  <br/>
  <br/>
 </p>
 <strong>
  Job Description
  <br/>
  <br/>
 </strong>
 <p>
  CapTech Machine Learning Engineers are responsible for designing and implementing data-driven solutions for our clients, with a specific focus on building and deploying scalable machine learning systems in enterprise environments. CapTech employees enjoy a collaborative environment and have many opportunities to learn from and share knowledge with other CapTech analysts, architects, and our clients.
  <br/>
  <br/>
 </p>
 <p>
  <strong>
   <em>
    Specific responsibilities for the Machine Learning Engineer position include:
    <br/>
    <br/>
   </em>
  </strong>
 </p>
 <ul>
  <li>
   Strategizing with clients, data scientists, engineers, and other members of cross-functional teams to implement end-to-end machine learning solutions and identify new machine learning and data science approaches to meet business needs
  </li>
  <li>
   Deconstructing client needs into data-driven processes/models and analytical measures.
  </li>
  <li>
   Analyzing and transforming large datasets hosted on a variety of enterprise-level data platforms (e.g., AWS, Azure, GCP).
  </li>
  <li>
   Designing, developing, and deploying advanced analytical solutions leveraging client data (e.g., recommender systems, natural language processing, risk scoring).
  </li>
  <li>
   Productionizing ML systems with a focus on optimization and scalability to satisfy clients&rsquo; requirements.
  </li>
  <li>
   Growing CapTech&rsquo;s Machine Learning and Data Science practices through delivering client presentations, writing proposals, attending various business development events, and leading teams of junior data scientists and engineers.
  </li>
 </ul>
 <p>
  <br/>
  <br/>
  <br/>
  <br/>
 </p>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor's degree or equivalent combination of education and experience.
  </li>
  <li>
   Hands-on experience manipulating and analyzing large (multi-billion record) data sets.
  </li>
  <li>
   Hands-on experience developing data-driven solutions using Python, Scala, or similar languages.
  </li>
  <li>
   Proficiency leveraging SQL, Spark, NoSQL, and/or cloud data processing frameworks in a production setting.
  </li>
  <li>
   Proficiency with containerization (e.g., Docker) and microservices.
  </li>
  <li>
   Proficiency with data warehousing tools/environments such as Snowflake, Databricks, Azure SQL, Amazon RDS
  </li>
  <li>
   Comfort and proficiency in framing data-driven problems from cross-industry business requirements.
  </li>
  <li>
   Experience applying analytical methods across multiple business domains (e.g., customer analytics, marketing, finance, digital channels)
  </li>
  <li>
   Hands-on experience implementing production-scale machine learning systems in one or more domains (i.e., personalization, natural language processing, computer vision).
  </li>
  <li>
   Knowledge of DevOps and automation best practices.
  </li>
  <li>
   Knowledge of statistics and statistical modeling methods.
  </li>
  <li>
   Knowledge of model management and model versioning best practices.
  </li>
  <li>
   Experience working with LLMs (e.g., GPT, Claude, Mistral, etc.) in production setting
  </li>
  <li>
   Experience with prompt engineering, MCP and RAG, and agentic AI architectures
  </li>
  <li>
   Strong understanding of conversational UX and prompt evaluation metrics
  </li>
  <li>
   Experience with agentic frameworks in practice (langchain, n8n, pydantic, etc.)
  </li>
  <li>
   Experience with multi-agent orchestration
  </li>
 </ul>
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 </p>
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 </p>
 <strong>
  Additional Information
  <br/>
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 </strong>
 <p>
  We want everyone at CapTech to be able to envision a lasting and rewarding career here, which is why we offer a variety of career paths based on your skills and passions.  You decide where and how you want to develop, and we help get you there with customizable career progression and a comprehensive benefits package to support you along the way.  Alongside our suite of traditional benefits encompassing generous PTO, health coverage, disability insurance, paid family leave and more, we&rsquo;ve launched extended benefits to help meet our employees&rsquo; needs.
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 </p>
 <ul>
  <li>
   CapTech is committed to providing a flexible work environment and helping our employees achieve a work-life balance that suits their individual needs. Employees must be available to work onsite in a client location or a CapTech office as requested. We allow CapTech employees to work remotely when compatible with CapTech and client needs.
  </li>
  <li>
   Learning &amp; Development &ndash; Programs offering certification and tuition support, digital on-demand learning courses, mentorship, and skill development paths
  </li>
  <li>
   Modern Health &ndash;A mental health and well-being platform that provides 1:1 care, group support sessions, and self-serve resources to support employees and their families through life&rsquo;s ups and downs
  </li>
  <li>
   Carrot Fertility &ndash;Inclusive fertility and family-forming coverage for all paths to parenthood &ndash; including adoption, surrogacy, fertility treatments, pregnancy, and more &ndash; and opportunities for employer-sponsored funds to help pay for care
  </li>
  <li>
   Fringe &ndash;A company paid stipend program for personalized lifestyle benefits, allowing employees to choose benefits that matter most to them &ndash; ranging from vendors like Netflix, Spotify, and GrubHub to services like student loan repayment, travel, fitness, and more
  </li>
  <li>
   Employee Resource Groups &ndash; Employee-led committees that embrace and incorporate diversity and inclusion into our day-to-day operations
  </li>
  <li>
   Philanthropic Partnerships &ndash; Opportunities to engage in partnerships and pro-bono projects that support our communities.
  </li>
  <li>
   401(k) Matching &ndash; Generous matching and no vesting period to help you continue to build financial wellness
  </li>
 </ul>
 <p>
  CapTech is an equal opportunity employer committed to fostering a culture of equality, inclusion and fairness &mdash; each foundational to our core values.  We strive to create a diverse environment where each employee is encouraged to bring their unique ideas, backgrounds and experiences to the workplace. For more information about our Diversity, Inclusion and Belonging efforts, click HERE.  As part of this commitment, CapTech will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact Laura Massa directly via email lmassa@captechconsulting.com.
  <br/>
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 </p>
 <p>
  At this time, CapTech cannot transfer nor sponsor a work visa for this position. Applicants must be authorized to work directly for any employer in the United States without visa sponsorship.
 </p>
</div>


Machine Learning / Data Science Engineer

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