Turing

Remote Scala developer jobs with U.S. companies

We, at Turing, are looking for experienced remote Scala developers who can build scalable applications according to the specifications. Here’s your opportunity to work with the best Silicon Valley companies and collaborate with top industry veterans across the globe.

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Job description

Job responsibilities

  • Analyze and experiment with upcoming trends in designing & coding
  • Maintain high quality technical documentation
  • Design, build and maintain applications in Scala
  • Support and lead design and development decisions with a focus on scalability, simplicity and maintainability
  • Develop efficient modules and shared libraries to solve common problems across projects
  • Test, analyze, and debug software applications

Minimum requirements

  • Bachelor’s/Master’s degree in Computer Science (or equivalent experience)
  • 3+ years of experience working with Scala (rare exceptions for highly skilled developers)
  • Strong knowledge of Java, Spark, PySpark, Python, API development and RESTful web services
  • Experience working with data stores like SQL/NoSQL, cloud object storage and data warehouses
  • Capable of documenting design changes into databases
  • Skilled at setting up and executing automated functional, UI and load/performance tests

Preferred skills

  • Experience with AWS, Big Data, Hadoop, and Hive
  • Experience in Git, user tools, build systems, and compilers
  • Excellent interpersonal and communication skills
  • Great team player with strong attention to detail

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    Fill in your basic details - Name, location, skills, salary, & experience.

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  4. Start working on your dream job

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How to become a Scala developer?

Scala is a functional, object-oriented programming language with a programming style that is both small and concise. Scala is a programming language that runs on the Java Virtual Machine (JVM) and is ideal for creating complicated applications. Scala has fewer lines of code than Java, is more type-safe, enables functional programming (FP), and surpasses Java in terms of object-oriented programming (OOP). A Scala developer's job is to design, develop, and maintain Scala-based applications. They also participate in any architectural development activities related to the application.

What is the scope in Scala development?

Scala is a popular programming language around the world. The programming language's scalability is the key reason for its appeal. It also employs the functional programming methodology, which aids the user in creating efficient applications. Its popularity is growing by the day due to its interoperability with Java and JVM support. You may be more productive as a result of its functional programming style, which hides complexity that could affect code quality. Software distribution and concurrency are easier with JVM since it is concurrent.
As a result, the Scala programming language offers a wide range of applications. Scala is also a good place to start if you want to pursue a career as a data scientist. It is a medium-difficulty language with a wide range of applications.

What are the roles and responsibilities of a Scala developer?

A Scala developer is a specialist in the Scala programming language, which is both object-oriented and high-level. They provide enterprise applications on the cloud, design, develop, and test technical solutions & components for businesses. Scala developers build code that adheres to app requirements, perform software analysis, and collaborate with other members of the software development team to verify that application designs are accurate. The primary responsibilities in Scala developer’s job are as follows –

  • Use Scala to create, build, and maintain applications.
  • Responsible for all architectural development efforts related to the application. Write code according to the app specification.
  • Perform a software analysis.
  • Work as part of a software development team to ensure that the application meets the requirements.
  • Application testing and debugging.
  • Any enhancements to application procedures and infrastructure should be recommended.
  • Effectively collaborate across teams.
  • Contribute to the enhancement of the team's performance.
  • Process of creating a document.

Scala programmers must be fluent in Scala as well as other object-oriented programming languages like Java, Python, and JavaScript. They must also have prior expertise in developing software. They must be well-versed in object-oriented programming (OOP) ideas, patterns and have good technical skills. Basic understanding of Spark, Hadoop, and MapReduce is also required. Scala programmers should be familiar with ETL architecture as well as public cloud platforms like AWS; they should also be well-versed in software development processes. Scala developers must have good communication and analytical skills in addition to the talents listed above. They must also be able to communicate facts succinctly and clearly.

How to become a Scala developer?

The amount of time it takes to learn Scala is determined by whether or not you are already familiar with Java. Scala will take you around a month to learn if you already know Java. It will take you two to three months to learn Java if you are not already familiar with it. According to several software professionals, Scala has a steep learning curve. In Scala, there are numerous ways to achieve things, and it's a language that encourages creativity and flexibility. If you're an experienced programmer, and especially if you're familiar with Java, this can be quite useful. Working with a language that has multiple ways of achieving the same thing can be tough if you are just getting started with programming. As you begin to study Scala, here are some big-picture steps to consider:

  • Recognize the two programming paradigms on which Scala is built. Scala is a programming language that combines functional and object-oriented programming paradigms. Before learning Scala, it's a good idea to understand the fundamentals of both.
  • Experiment with the Scala syntax. Explore the Scala syntax in your browser before installing everything you need for Scala on your PC.
  • Investigate the Scala installation procedure. It is rather simple to install everything you need to start creating code in other languages, such as Python, this is not the case with Scala. You must first install Java on your computer before proceeding to install the SBT (Scala Build Tool).
  • Install an IDE or be ready to write Scala from the command line. You can get an IDE (Integrated Development Environment) with Scala plug-ins, such as JetBrains' IntelliJ or Eclipse's Eclipse. You can also utilize your command line to write programs, as suggested in the getting started tutorial.
  • Make use of the various resources accessible to you. Once you've set up your Scala programming environment, use tools like the Scala documentation's 'getting started' section and the resources below to get started developing Scala programs.
  • Try to craft a Scala developer resume that provides enough information to recruiters to present you as a viable applicant for important projects

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Skills required to become a Scala developer

The first step is to learn the core abilities that will help you land a high-paying Scala developer job. Let's take a look at what you should be aware of.

1. Knowledge of Java and Python

Python is a dynamically typed and interpreted language, whereas Java is statically typed and compiled. Java is faster at runtime and easier to debug because of this one difference, while Python is easier to use and read. Python's appeal is due in great part to its communicability; people simply comprehend it more easily. It comes with a plethora of Python libraries, so a novice coder won't have to start from scratch. Because Java is old and still frequently used, it has a large number of libraries and a supportive community. As a Scala developer you should have a good knowledge of these languages.

2. Spark, Hadoop and MapReduce

To be proficient in the Scala developer job, you must be familiar with Spark, Hadoop and MapReduce. Hadoop had been the unquestioned champion of big data for years, until Spark came along. Apache Spark has been igniting the world of big data since its initial release in 2014. Some observers say Spark has heralded the dawn of a new age in big data, thanks to its user-friendly APIs and projected speeds of up to 100 times quicker than Hadoop MapReduce.

3. ETL architecture

The data integration process relies heavily on ETL (extract, transform, and load). It's the backbone of today's business intelligence and analytics workloads, moving and manipulating data between source and target in an effective manner. But understanding how ETL works is one thing; building an effective ETL architecture for your company is quite another. ETL architecture, like real-world building projects, requires a strategy and a solid foundation to ensure that your workflow meets your current demands and scales with you as you develop

4. AWS

Amazon Web Services (AWS) is a comprehensive cloud computing platform that includes infrastructure as a service (IaaS), platform as a service (PaaS), and packaged software as a service (SaaS). AWS services can give resources like compute power, database storage, and content delivery to a business. AWS is separated into a number of services, each of which can be customised in a variety of ways based on the user's requirements. Users should be able to access configuration options and particular server mappings for an AWS service.

5. Object-oriented programming concepts and patterns

Object-Oriented Programming, or OOPs, is a term that refers to programming languages that employ objects. Object-oriented programming includes inheritance, hiding, polymorphism, and other real-world principles. The basic goal of OOP is to connect data and the functions that operate on it so that no other part of the code may access it except that function.

Interested in remote Scala developer jobs?

Become a Turing developer!

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How to get remote Scala developer jobs?

You must develop a sound job-search strategy while getting as much real-world experience as feasible. Before you start looking for jobs, think about what you're looking for and how you'll utilise that information to narrow down your search. It's all about getting hands-on and putting your talents to work when it comes to convincing companies that you're job-ready. As a result, it's critical to continue learning and growing. The more projects you work on, whether open source, volunteer, or freelancing, the more you'll have to discuss in an interview.
Turing has the greatest remote Scala developer jobs that are tailored to your professional goals as a Scala developer. Working on difficult technical and business problems with cutting-edge technologies will help you grow quickly. Get full-time, long-term remote Scala developer job with greater income and career progression by joining a network of the world's greatest developers.

Why become a Scala developer at Turing?

Elite US jobs

Long-term opportunities to work for amazing, mission-driven US companies with great compensation.

Career growth

Work on challenging technical and business problems using cutting-edge technology to accelerate your career growth.

Exclusive developer community

Join a worldwide community of elite software developers.

Once you join Turing, you’ll never have to apply for another job.

Turing's commitments are long-term and full-time. As one project draws to a close, our team gets to work identifying the next one for you in a matter of weeks.

Work from the comfort of your home

Turing allows you to work according to your convenience. We have flexible working hours and you can work for top US firms from the comfort of your home.

Great compensation

Working with top US corporations, Turing developers make more than the standard market pay in most nations.

How much does Turing pay their Scala developers?

Every Scala developer at Turing is free to determine their own rate. Turing, on the other hand, will recommend a wage at which we are confident we can offer you a rewarding and long-term opportunity. Our suggestions are based on our analysis of market conditions and the demand we perceive from our clients.

Frequently Asked Questions

A Scala developer is an experienced professional in object-oriented and high-level programming languages. The main responsibilities usually include designing, developing, and testing technical components for organizations in the cloud.

Turing is an AGI infrastructure company specializing in post-training large language models (LLMs) to enhance advanced reasoning, problem-solving, and cognitive tasks. Founded in 2018, Turing leverages the expertise of its globally distributed technical, business, and research experts to help Fortune 500 companies deploy customized AI solutions that transform operations and accelerate growth. As a leader in the AGI ecosystem, Turing partners with top AI labs and enterprises to deliver cutting-edge innovations in generative AI, making it a critical player in shaping the future of artificial intelligence.

After uploading your resume, you will have to go through the three tests -- seniority assessment, tech stack test, and live coding challenge. Once you clear these tests, you are eligible to apply to a wide range of jobs available based on your skills.

On average, Scala developers can easily earn around 15,000 to 45,000 USD while working from home with top US organizations. The payscale can depend on different factors like seniority, years of professional experience, tech stack, and location. If you’re looking to take your career ahead as a Scala development specialist, you can try Turing jobs and grab the best opportunities.

We, at Turing, hire remote developers for over 100 skills like React/Node, Python, Angular, Swift, React Native, Android, Java, Rails, Golang, PHP, Vue, among several others. We also hire engineers based on tech roles and seniority.

Communication is crucial for success while working with American clients. We prefer candidates with a B1 level of English i.e. those who have the necessary fluency to communicate without effort with our clients and native speakers.

Scala developers are some of the most well-paid professionals as it supports a wide range of development solutions. From applications to machine learning, to webpages and Android development, Scala can get almost every job done.

Our unique differentiation lies in the combination of our core business model and values. To advance AGI, Turing offers temporary contract opportunities. Most AI Consultant contracts last up to 3 months, with the possibility of monthly extensions—subject to your interest, availability, and client demand—up to a maximum of 10 continuous months. For our Turing Intelligence business, we provide full-time, long-term project engagements.

No, the service is absolutely free for software developers who sign up.

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Leadership

In a nutshell, Turing aims to make the world flat for opportunity. Turing is the brainchild of serial A.I. entrepreneurs Jonathan and Vijay, whose previous successfully-acquired AI firm was powered by exceptional remote talent. Also part of Turing’s band of innovators are high-profile investors, such as Facebook's first CTO (Adam D'Angelo), executives from Google, Amazon, Twitter, and Foundation Capital.

Equal Opportunity Policy

Turing is an equal opportunity employer. Turing prohibits discrimination and harassment of any type and affords equal employment opportunities to employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, age, disability status, protected veteran status, or any other characteristic protected by law.

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briefcase
Principal AI Engineer - US NYC

Principal AI Engineer

Location: US(NYC)- 3(WFO)

Employment Type: Full Time (Overlapping EST)

Experience Level: Staff/Principal (8–14 years)


About the Role

Turing is hiring a Staff/Principal AI Engineer to lead enterprise-scale agentic AI implementations for Fortune 500 clients. This is a hands-on engineering role focused on designing and shipping autonomous, tool-calling AI systems — agents that reason over enterprise context, invoke real systems through secure interfaces, and operate reliably at scale under strict latency, cost, and governance constraints.

You will own these systems end to end: the data pipelines feeding them, the backend services around them, the agent orchestration layer, the evaluation harness that keeps them honest, and the cloud infrastructure they run on. We are looking for engineers with genuine software engineering and data science depth who have taken agentic systems all the way to production.

What We're Looking For

Engineering foundation

  • 8–14 years of software engineering experience, with strong hands-on large-scale Python
  • Working depth in at least one systems or backend language — Go, Rust, Java, or C/C++ — and the judgment to know when to reach for it
  • Strong data structures and algorithms.
  • Strong understanding of APIs, microservices, and system design
  • Hands-on experience building and operating data pipelines and production-grade distributed systems.

Agentic AI and LLMs

  • 2+ years of hands-on LLM engineering, with at least couple agentic system you designed and took to production
  • Production experience with agent frameworks — LangGraph, Google ADK, CrewAI, Claude Agent SDK, or equivalent — and the fluency to move between them as the ecosystem evolves
  • Experience building MCP (Model Context Protocol) servers and tool-calling interfaces
  • RAG from first principles: chunking strategy, embeddings, vector and hybrid retrieval, reranking, and response validation
  • Strong experience with vector databases (Milvus, Pinecone, Weaviate, FAISS, etc. or cloud equivalents)
  • Design of guardrails and reliability patterns — validators, policy checks, self-correction loops, deterministic fallbacks, circuit breakers, and rollback paths

Optimization

  • Deep familiarity with token optimization and context-window management — context shaping, pruning, and compaction
  • Latency and cost optimization through caching, model routing, batching, streaming, and parallel tool calls
  • Performance testing and tuning systems against defined SLOs

Evaluation

  • Experience building evaluation frameworks for LLM systems — offline eval sets, continuous online evaluation, and regression detection
  • Instrumentation and traceability suitable for regulated enterprise environments using tools like LangSmith, Langfuse, etc.

Cloud

  • Hands-on AWS: containerized services (ECS/EKS), serverless (Lambda), data services (S3, DynamoDB, Redshift) and orchestration (Step Functions); Azure or GCP equivalents also valued
  • Familiarity with CI/CD pipelines and DevOps practices
  • Infrastructure as code with Terraform or CloudFormation, and mature CI/CD practice

Working traits

  • Strong analytical problem-solving with a bias to ownership and urgency
  • Clear cross-team communication, working directly with client stakeholders to translate business problems into technical roadmaps
  • Able to work productively in ambiguity from system-level documentation and ramp quickly in unfamiliar codebases

Good to Have

  • Experience with managed AI platforms — Amazon Bedrock, Vertex AI, Azure AI — paired with fluency in the underlying fundamentals

Roles & Responsibilities

  • Design and build agentic systems: Lead the architecture and implementation of tool-calling agents that combine retrieval, structured reasoning, and secure action execution with least-privilege access.
  • Productionize LLM applications: Build retrieval pipelines, prompt synthesis, response validation, and self-correction loops, backed by rigorous evaluation.
  • Own the full stack: Deliver the data pipelines, backend services, distributed compute, and orchestration layer that agentic systems depend on — not only the model invocation.
  • Engineer for reliability and governance: Build validator models, adversarial test suites, and policy checks; enforce deterministic fallbacks and rollback strategies; instrument continuous evaluation.
  • Optimize for cost and latency: Drive measurable improvements in token efficiency, response time, and unit economics against defined SLOs.
  • Codebase ownership: Build, maintain, and review high-quality Python and SQL, with an emphasis on reusable components, scalability, and performance.
  • Cloud integration: Deploy AI applications on AWS, Azure, or GCP with optimized resource usage and robust CI/CD.
  • Cross-functional collaboration: Partner with product owners, data scientists, and business SMEs to define requirements and deliver impactful AI products.
  • Mentoring and technical leadership: Set engineering standards and share knowledge across the team, raising the bar on AI and software engineering practice.
Finance
10K+ employees
PythonGoRust+ 4
briefcase
Lead Edge AI & Computer Vision Engineer

Lead Edge AI & Computer Vision Engineer

  • Location: USA [with regular on-site travel required to client site]
  • Target Start Date: 1 Sep
  • Time Commitment: 8 weeks full-time
  • Experience Level: 12–15+ Years

Core Objective: Architect, benchmark, and optimize an end-to-end computer vision and low-latency execution pipeline—combining spatial geometric math with low-level C++/CUDA acceleration directly on NVIDIA Jetson embedded edge hardware (Orin NX / AGX Orin) to achieve sub-10 ms processing latency.

Key Responsibilities

  1. Model Selection & Spatial Math: Evaluate real-time detection topologies (e.g. YOLO) at 100+ FPS and build 2D perspective homography unwarping, lens undistortion, and spatial algorithms to convert pixel coordinates into physical millimeter units within tight error bounds (millimeter level accuracy).
  2. TensorRT INT8 Acceleration: Execute Post-Training Quantization to compile PyTorch/ONNX models into high-throughput TensorRT INT8/FP16 engines on Jetson Orin hardware without accuracy degradation.
  3. Zero-Copy Memory Architecture:  Engineer zero-copy memory pipelines using NVIDIA Memory Management and DMA transfers to eliminate bottlenecks.
  4. Compiled C++ Execution & I/O: Build compiled C++17 execution frameworks with multi-threaded lock-free ring buffers and non-blocking asynchronous socket communication.
  5. Nsight Profiling & Roadmapping: Instrument stage-by-stage pipeline latency using NVIDIA Nsight Systems/NVTX markers to bound tail latency, author feasibility reports, and design technical roadmaps.

Key Qualifications & Experience

  1. Full-Stack Edge AI Experience: 12–15+ years of experience bridging real-time computer vision algorithm design, spatial geometry, and low-level C++/CUDA execution on embedded edge hardware.
  2. NVIDIA Jetson Ecosystem: Deep expertise in Jetson embedded platforms (Orin NX, AGX Orin, L4T, power profiles, core pinning) and a proven track record compiling/tuning TensorRT FP16/INT8 engines via PTQ/QAT.
  3. Optical & Spatial Geometry: Expertise in 2D/3D camera calibration, perspective homography transformations, lens distortion modeling, and millimeter sizing math in industrial settings.
  4. Low-Latency Systems Engineering: Expertise in zero-copy shared memory, DMA frame buffers, lock-free queues, custom CUDA plugins, and microsecond profiling via Nsight Systems and NVTX markers.
  5. Tooling & Industrial I/O: Proficiency in C++17, Python, PyTorch, OpenCV, CUDA, non-blocking asynchronous sockets (UDP, PLC integration), and building automated dataset benchmarking harnesses.
Manufacturing
10K+ employees
C++CUDANVIDIA Omniverse+ 5
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