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Junior Machine Learning Jobs in Washington (NOW HIRING)

Senior Staff Machine Learning Engineer

Bethesda, MD · On-site

$111K - $153K/yr

... Machine Learning Engineer to help shape how Generative AI enhances customer and associate ... Mentor engineers and junior tech leads; codify best practices; contribute to internal documentation ...

Applied Research Associates, Inc. (ARA) has an outstanding opportunity for a Junior Data Scientist ... machine learning and statistical models, and exploratory data analysis. • Create basic ...

Mentor more junior team members professionally to help them realize their full potential * Consistently share best practices and improve processes within and across teams Qualifications * Fluency and ...

Group Nine LLC is seeking a Data Scientist to develop and maintain data analytics solutions and machine learning algorithms. The role involves mentoring junior data scientists, enhancing the data ...

Parsons Corporation is currently searching for a full-time Software Developer Junior position at ... Work with tools and frameworks such as AWS, Docker, Kubernetes, and machine learning libraries (e.g ...

Junior Data Engineer

Mclean, VA · On-site

$100K - $120K/yr

Junior Data Engineer Candidates can be located in DC area, Tampa FL or Fayetteville NC The ... Ever-expanding technology like IoT, machine learning, and artificial intelligence means that there ...

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Junior Machine Learning information

See Washington salary details

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How much do junior machine learning jobs pay per hour?

As of Jun 13, 2026, the average hourly pay for junior machine learning in Washington is $30.53, according to ZipRecruiter salary data. Most workers in this role earn between $18.51 and $37.55 per hour, depending on experience, location, and employer.

What is the difference between Junior Machine Learning vs Data Scientist?

AspectJunior Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some experience with ML toolsBachelor's or Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentEntry-level projects, supervised tasks, team collaborationAdvanced analysis, model development, cross-functional teams
Industry UsageCommon in tech companies, startups, research labsWidespread across industries like finance, healthcare, tech

Junior Machine Learning roles focus on foundational ML tasks and learning on the job, while Data Scientists handle complex data analysis, model building, and strategic insights. The roles differ mainly in experience level and scope of responsibilities, but both require strong technical skills and familiarity with data tools.

What does a Junior Machine Learning Engineer do?

A Junior Machine Learning Engineer assists in the development and implementation of machine learning models and algorithms under the supervision of more experienced engineers. They typically help with data collection, cleaning, feature engineering, model training, and evaluation. Junior engineers may also write code, test prototypes, and contribute to improving model performance while learning best practices in the field. Their role often involves collaborating with data scientists and software engineers to integrate machine learning solutions into products or services.

What engineers make $500,000?

Senior engineers in fields like software, data engineering, or specialized roles such as machine learning engineers can earn $500,000 or more annually, especially with experience, advanced skills, and in high-demand industries. Compensation often includes base salary, bonuses, and stock options, particularly at large tech companies or startups with significant funding.

What types of projects and tasks can a Junior Machine Learning professional typically expect to work on in their first year?

As a Junior Machine Learning professional, you’ll often support senior data scientists and engineers by preparing data, implementing basic algorithms, and assisting with model evaluation. Your daily tasks may include data cleaning, feature engineering, running experiments, and writing code to automate data pipelines. You might also help document processes and present your findings to team members. While the work is often collaborative, you’ll have opportunities to take ownership of smaller projects and progressively contribute to larger initiatives as you gain experience.

Can I get into AI with no experience?

Junior Machine Learning roles typically require some foundational knowledge of programming, mathematics, and data analysis. While prior experience is often preferred, beginners can enter the field by learning relevant skills through online courses, tutorials, and projects, and by gaining familiarity with tools like Python and machine learning frameworks. Building a portfolio and obtaining certifications can also improve chances of entry-level employment.

Which 3 jobs will survive AI?

Junior Machine Learning roles are likely to persist as they require specialized knowledge, critical thinking, and domain expertise that AI cannot fully replicate. Jobs involving complex problem-solving, creativity, and human interaction, such as data scientists, AI ethics specialists, and AI system trainers, are also expected to remain in demand. Continuous learning and adapting to new tools will be essential for these roles to stay relevant.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often requiring advanced skills in deep learning, data science, and experience with tools like TensorFlow or PyTorch. These positions usually involve leadership responsibilities, extensive expertise, and may include stock options or bonuses as part of compensation packages.

What are the key skills and qualifications needed to thrive as a Junior Machine Learning Engineer, and why are they important?

To thrive as a Junior Machine Learning Engineer, you need a solid understanding of programming (especially Python), basic statistics, linear algebra, and familiarity with machine learning concepts, typically supported by a relevant degree or coursework. Proficiency in tools and frameworks like scikit-learn, TensorFlow, PyTorch, and version control systems such as Git is often expected. Strong problem-solving abilities, curiosity, and effective communication are crucial soft skills for collaborating with teams and explaining technical concepts. These skills and qualities are important because they enable you to contribute effectively to building, testing, and improving machine learning models in real-world applications.
What are the most commonly searched types of Machine Learning jobs in Washington? The most popular types of Machine Learning jobs in Washington are:
What are popular job titles related to Junior Machine Learning jobs in Washington? For Junior Machine Learning jobs in Washington, the most frequently searched job titles are:
What cities in Washington are hiring for Junior Machine Learning jobs? Cities in Washington with the most Junior Machine Learning job openings:
Infographic showing various Junior Machine Learning job openings in Washington as of June 2026, with employment types broken down into 1% As Needed, 96% Full Time, 2% Part Time, and 1% Contract. Highlights an 88% Physical, 1% Hybrid, and 11% Remote job distribution, with an average salary of $63,503 per year, or $30.5 per hour.
Senior Staff Machine Learning Engineer

Senior Staff Machine Learning Engineer

GEICO

Bethesda, MD • On-site

$111K - $153K/yr

Full-time

Retirement

Posted 5 days ago


GEICO rating

8.1

Company rating: 8.1 out of 10

Based on 351 frontline employees who took The Breakroom Quiz

133rd of 261 rated insurance


Job description

At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.
Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers' expectations while making a real impact for our company through our shared purpose.
When you join our company, we want you to feel valued, supported and proud to work here. That's why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers.
At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities. Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers' expectations while making a real impact for our company through our shared purpose. When you join our company, we want you to feel valued, supported and proud to work here. That's why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers
GEICO is seeking a Senior Staff Machine Learning Engineer to help shape how Generative AI enhances customer and associate experiences across the enterprise. This is a hands-on technical role who will be leading the strategy, architecture, and delivery of ML systems for the Claims organization-designing predictive models, robust data/feature pipelines, and production-grade MLOps to drive measurable business outcomes.
You will work alongside engineering teams, data scientists, and product leaders to design, build, and integrate AI-powered capabilities that automate workflows, improve decision-making, and elevate user experience. You will contribute to a culture of learning, curiosity, and innovation while growing your expertise in cutting-edge AI technologies
About the role
  • Staff+ individual contributor role focused on end-to-end ML: data and feature engineering, modeling, deployment, monitoring, and continuous improvement.
  • Partner with Claims Operations, Product, and Engineering to deliver ML capabilities such as severity/triage predictions, claim outcome forecasting, and automation accelerators.
  • GenAI (e.g., LLMs and agentic workflows) may be leveraged where it augments ML systems; strong ML depth is primary.

What you'll do
  • Own ML platform architecture: data/feature pipelines, experiment tracking, model registries, serving layers, offline/online evaluation, and observability.
  • Define standards for reliability, performance, cost efficiency, security, governance, and model risk management across ML services.
  • Lead design and implementation of models across classical ML and deep learning (e.g., gradient boosted trees, sequence models, Transformers for tabular/time-series/NLP where relevant).
  • Translate business goals into measurable ML objectives and experiment plans; ensure robust offline metrics and real-world impact.
  • Build scalable training and inference pipelines; establish CI/CD for ML, automated evaluations, canary releases, and rollback strategies.
  • Implement monitoring for data quality, drift, fairness, latency, reliability, and cost; lead incident response and postmortems.
  • Partner with Claims, Product, Data Science, Platform/SRE, Security, and Legal/Compliance to gather requirements, define scope, and prioritize backlogs.
  • Maintain pragmatic technical roadmaps balancing business outcomes, release timelines, and engineering excellence.
  • Own build-vs-buy decisions and tooling/service selection (speed to market, extensibility, TCO); guide platform evolution with clear architectural principles.
  • Lead experienced engineers through complex platform implementations; drive system-wide architectural improvements and reliability practices.
  • Mentor engineers and junior tech leads; codify best practices; contribute to internal documentation and promote enterprise-wide ML standards.
  • Where appropriate, collaborate on retrieval-augmented workflows, prompt/context management, and LLM evaluation and safety guardrails to complement ML systems.

Minimum qualifications
  • Bachelor's degree or above in Computer Science, Engineering, Statistics, or related field.
  • 10+ years of professional software development experience using at least two general-purpose languages (e.g., Java, C++, Python, C#).
  • 10+ years architecting, designing, and building multi-component ML platforms leveraging open-source/cloud-agnostic components:
    • Search/vector: ElasticSearch, Qdrant (as applicable to ML features and retrieval)
    • Data warehouse/lakehouse: Snowflake; familiarity with Parquet/Delta/Iceberg
    • Streaming: Kafka; plus Flink/Spark Streaming experience
    • Datastores: PostgreSQL; NoSQL (MongoDB, Cassandra)
    • Distributed compute: Spark, Ray
    • Workflow orchestration: Airflow, Temporal
  • 6+ years managing end-to-end SDLC for ML systems: version control, CI/CD, Kubernetes, testing (unit/integration/data/ML eval), monitoring/alerting, production support.
  • 6+ years working with cloud providers (Azure and/or AWS) in production ML contexts.

Preferred qualifications (GenAI as a plus)
  • Experience leveraging or fine-tuning LLMs (e.g., GPT, Llama, Mistral, Claude) to augment ML workflows, retrieval, or claims-facing tooling.
  • Hands-on with MLOps tooling: MLflow/Kubeflow, model registries, feature stores (e.g., Feast), experiment tracking, A/B testing and online evaluation frameworks.
  • Observability: Prometheus/Grafana, OpenTelemetry; SLO-driven operations and incident management.
  • Model safety, fairness, explainability (e.g., SHAP/LIME), and regulatory compliance; familiarity with model risk management practices.
  • Insurance/financial services domain experience: claims automation, fraud detection, risk modeling, subrogation, severity/triage, and regulatory stewardship.
  • Experience with high-throughput, low-latency inference and real-time feature pipelines.

#LI-JK1
Annual Salary
$150,000.00 - $300,000.00
The above annual salary range is a general guideline. Multiple factors are taken into consideration to arrive at the final hourly rate/ annual salary to be offered to the selected candidate. Factors include, but are not limited to, the scope and responsibilities of the role, the selected candidate's work experience, education and training, the work location as well as market and business considerations.
GEICO will consider sponsoring a new qualified applicant for employment authorization for this position.
The GEICO Pledge:
Great Company: At GEICO, we help our customers through life's twists and turns. Our mission is to protect people when they need it most and we're constantly evolving to stay ahead of their needs.
We're an iconic brand that thrives on innovation, exceeding our customers' expectations and enabling our collective success. From day one, you'll take on exciting challenges that help you grow and collaborate with dynamic teams who want to make a positive impact on people's lives.
Great Careers: We offer a career where you can learn, grow, and thrive through personalized development programs, created with your career - and your potential - in mind. You'll have access to industry leading training, certification assistance, career mentorship and coaching with supportive leaders at all levels.
Great Culture: We foster an inclusive culture of shared success, rooted in integrity, a bias for action and a winning mindset. Grounded by our core values, we have an an established culture of caring, inclusion, and belonging, that values different perspectives. Our teams are led by dynamic, multi-faceted teams led by supportive leaders, driven by performance excellence and unified under a shared purpose.
As part of our culture, we also offer employee engagement and recognition programs that reward the positive impact our work makes on the lives of our customers.
Great Rewards: We offer compensation and benefits built to enhance your physical well-being, mental and emotional health and financial future.
  • Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family's overall well-being.
  • Financial benefits including market-competitive compensation; a 401K savings plan vested from day one that offers a 6% match; performance and recognition-based incentives; and tuition assistance.
  • Access to additional benefits like mental healthcare as well as fertility and adoption assistance.
  • Supports flexibility- We provide workplace flexibility as well as our GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year.

The equal employment opportunity policy of the GEICO Companies provides for a fair and equal employment opportunity for all associates and job applicants regardless of race, color, religious creed, national origin, ancestry, age, gender, pregnancy, sexual orientation, gender identity, marital status, familial status, disability or genetic information, in compliance with applicable federal, state and local law. GEICO hires and promotes individuals solely on the basis of their qualifications for the job to be filled.
GEICO reasonably accommodates qualified individuals with disabilities to enable them to receive equal employment opportunity and/or perform the essential functions of the job, unless the accommodation would impose an undue hardship to the Company. This applies to all applicants and associates. GEICO also provides a work environment in which each associate is able to be productive and work to the best of their ability. We do not condone or tolerate an atmosphere of intimidation or harassment. We expect and require the cooperation of all associates in maintaining an atmosphere free from discrimination and harassment with mutual respect by and for all associates and applicants.

What GEICO employees say

Pay

Benefits

Hours and flexibility

Workplace

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GEICO logo

About GEICO

Sourced by ZipRecruiter

GEICO is built on ingenuity, perseverance, innovation, resilience, and hard, honest work. From its humble beginnings in the midst of the Great Depression to its current place as one of the most successful companies in the nation, GEICO represents a quintessential American success story. At GEICO, we love that our associates are proud goal-seekers, and that's why we believe in celebrating their milestones and rewarding their achievements. Throughout the year we reward performance and accomplishments, host programs that recognize personal successes, and acknowledge innovation, service, and leadership.

Industry

Insurance services

Company size

10,000+ Employees

Headquarters location

Chevy Chase, MD, US

Year founded

1936