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Machine Learning Engineer Quantization Jobs in Portage, IN

IMC

Machine Learning Researcher

Chicago, IL

... machine learning & deep learning to solve challenging trading problems. This role is part of a ... The ideal candidate will have experience working with other researchers and engineers to build and ...

Varsity Tutors

Machine Learning Tutor

Chicago, IL · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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Machine Learning Engineer Quantization information

See Portage, IN salary details

$28.9K

$118.1K

$177.5K

How much do machine learning engineer quantization jobs pay per year?

As of May 31, 2026, the average yearly pay for machine learning engineer quantization in Portage, IN is $118,133.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,100.00 and $142,200.00 per year, depending on experience, location, and employer.

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

To thrive as a Machine Learning Engineer Quantization, you need a solid background in machine learning, deep learning, and computer science, typically supported by a degree in a related field. Familiarity with quantization techniques, frameworks such as TensorFlow Lite or PyTorch, and experience with hardware accelerators are crucial. Strong problem-solving skills, attention to detail, and effective collaboration set top performers apart. These capabilities are vital for efficiently deploying high-performing models on resource-constrained devices and ensuring scalable, real-world AI solutions.

What are some common challenges Machine Learning Engineers face when implementing quantization techniques in production models?

Machine Learning Engineers working on quantization often encounter challenges such as balancing reduced model size and computational efficiency with maintaining acceptable accuracy levels. Adapting quantization methods to different hardware platforms can also require significant testing and optimization. Additionally, engineers must frequently address compatibility issues with existing deployment pipelines and ensure that quantization-aware training is properly integrated to minimize performance degradation. Collaboration with hardware and software teams is essential to streamline deployment and achieve optimal results.

What does a Machine Learning Engineer Quantization do?

A Machine Learning Engineer specializing in quantization focuses on optimizing machine learning models by reducing their size and computational requirements without significantly sacrificing accuracy. This involves converting model parameters and computations from high-precision formats (like 32-bit floating point) to lower-precision formats (such as 8-bit integers). Quantization enables faster inference, lower memory usage, and allows models to run efficiently on edge devices and mobile platforms. These engineers work closely with data scientists and hardware teams to implement, test, and validate quantized models in production environments.

What is the difference between Machine Learning Engineer Quantization vs Data Scientist?

AspectMachine Learning Engineer QuantizationData Scientist
Required CredentialsBachelor's or master's in CS, ML, or related; certifications in ML or AIBachelor's or master's in statistics, CS, or related; certifications in data analysis or statistics
Work EnvironmentDeveloping optimized ML models, deploying quantized models for efficiencyAnalyzing data, building predictive models, interpreting results
Industry UsageTech companies, AI hardware firms, embedded systemsFinance, healthcare, marketing, research institutions

Machine Learning Engineer Quantization focuses on optimizing ML models for deployment efficiency, often working closely with hardware and software teams. Data Scientists analyze data and build models for insights. While both roles require ML knowledge, quantization engineers specialize in model compression techniques, whereas data scientists focus on data analysis and interpretation.

What are popular job titles related to Machine Learning Engineer Quantization jobs in Portage, IN? For Machine Learning Engineer Quantization jobs in Portage, IN, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Portage, IN look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Portage, IN are:
Machine Learning Engineer Quantization jobs near you
Lead Machine Learning / Data Science Engineer

Lead Machine Learning / Data Science Engineer

CapTech Consulting

Chicago, IL

$57.50 - $76/hr

Full-time

Medical, Retirement, PTO

Posted 28 days ago

Job description

Company Description

CapTech is an award-winning consulting firm that collaborates with clients to achieve what’s possible through the power of technology. At CapTech, we’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.

Job Description

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.

Specific responsibilities for the Lead Machine Learning Engineer position include:

  • 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
  • Provide technical leadership and collaborate within and across teams to ensure that the overall technical solution is aligned with the customer needs. 
  • Deconstructing client needs into data-driven processes/models and analytical measures.
  • Analyzing and transforming large datasets hosted on a variety of enterprise-level data platforms (e.g., AWS, Azure, GCP).
  • Designing, developing, and deploying advanced analytical solutions leveraging client data (e.g., recommender systems, natural language processing, risk scoring).
  • Productionizing ML systems with a focus on optimization and scalability to satisfy clients’ requirements.
  • Growing CapTech’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.
Qualifications
  • 7+ years of experience delivering data engineering and machine learning solutions on cloud platforms 
  • Bachelor's degree or equivalent combination of education and experience.
  • Experience providing technical leadership and mentoring other engineers in data engineering space 
  • Hands-on experience manipulating and analyzing large (multi-billion record) data sets.
  • Hands-on experience developing data-driven solutions using Python, Scala, or similar languages.
  • Proficiency leveraging SQL, Spark, NoSQL, and/or cloud data processing frameworks in a production setting.
  • Proficiency with containerization (e.g., Docker) and microservices.
  • Proficiency with data warehousing tools/environments such as Snowflake, Databricks, Azure SQL, Amazon RDS
  • Comfort and proficiency in framing data-driven problems from cross-industry business requirements.
  • Experience applying analytical methods across multiple business domains (e.g., customer analytics, marketing, finance, digital channels)
  • Hands-on experience implementing production-scale machine learning systems in one or more domains (i.e., personalization, natural language processing, computer vision).
  • Knowledge of DevOps and automation best practices.
  • Knowledge of statistics and statistical modeling methods.
  • Knowledge of model management and model versioning best practices.
  • Experience working with LLMs (e.g., GPT, Claude, Mistral, etc.) in production setting 
  • Experience with prompt engineering, MCP and RAG, and agentic AI architectures 
  • Strong understanding of conversational UX and prompt evaluation metrics 
  • Experience with agentic frameworks in practice (langchain, n8n, pydantic, etc.)
  • Experience with multi-agent orchestration

Additional Information

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’ve launched extended benefits to help meet our employees’ needs. 

  • 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.
  • Learning & Development – Programs offering certification and tuition support, digital on-demand learning courses, mentorship, and skill development paths
  • Modern Health –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’s ups and downs
  • Carrot Fertility –Inclusive fertility and family-forming coverage for all paths to parenthood – including adoption, surrogacy, fertility treatments, pregnancy, and more – and opportunities for employer-sponsored funds to help pay for care
  • Fringe –A company paid stipend program for personalized lifestyle benefits, allowing employees to choose benefits that matter most to them – ranging from vendors like Netflix, Spotify, and GrubHub to services like student loan repayment, travel, fitness, and more
  • Employee Resource Groups – Employee-led committees that embrace and incorporate diversity and inclusion into our day-to-day operations
  • Philanthropic Partnerships – Opportunities to engage in partnerships and pro-bono projects that support our communities. 
  • 401(k) Matching – Generous matching and no vesting period to help you continue to build financial wellness

CapTech is an equal opportunity employer committed to fostering a culture of equality, inclusion and fairness — 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.

CapTech supports Equal Pay for all. In addition, in the State of Illinois we are committed to Equal Pay for ALL in accordance with the Illinois Equal Pay Act. The base pay range for this role is: $90,000 - $200,000. 

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. Â